Location: San Francisco, CA | New York City, NY | Washington, DC
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the role
As a Safeguards Enforcement Analyst on the account abuse team, you'll build and execute enforcement workflows that keep our products safe, with a focus on detecting and mitigating potential harm. Your initial focus will be account compromise: Anthropic's enforcement systems have to distinguish customers whose accounts have been compromised from actors abusing the platform — and today those two populations can look identical in the data. Stolen credentials and leaked keys are a growing abuse vector, and the collateral damage from enforcement against them lands on legitimate users. You'll own this problem end to end: detection, revocation, user notification, remediation, and the criteria for restoring access — turning what is today ad hoc incident response into a scalable, repeatable program.
This position may expand into broader areas of enforcement over time. Safety is core to our mission, and you'll help shape policy enforcement so that our users can safely interact with and build on top of our products in a harmless, helpful, and honest way.
Key responsibilities
Investigate credential-compromise incidents across first-party and third-party platforms, tracing actor behavior across accounts and surfaces
Design and operate remediation workflows for compromised accounts: revocation, customer notification, and standards for restoring access
Partner with Engineering and Data Science teams to improve how we separate compromised-customer traffic from willful abuse
Enforce usage policies with a focus on detecting and mitigating potentially harmful use of AI systems
Work with threat intelligence on emerging credential-abuse patterns and the actors behind them
Support the Safeguards policy design team by providing detailed feedback on policy gaps based on real enforcement scenarios
Keep up to date with emerging AI policy enforcement best practices, and use these to inform our decision-making and workflows
Write the policy framework for compromise scenarios, including cases where Anthropic can't independently verify a customer's security posture
Act as the enforcement SME when account compromise intersects with active abuse investigations
Minimum qualifications
Experience in trust and safety, fraud investigation, security operations, or a related field
Subject matter expertise in one or more of: account takeover, credential abuse, session security, or incident response
Experience designing or operating enforcement, remediation, or customer-recovery flows — not just detection
Comfort using data (SQL or similar tools) to trace actor behavior across accounts and to measure what's working
A thoughtful perspective on the tension between protecting the platform and restoring access for legitimate compromised customers
Strong written communication skills, with experience producing clear briefs about messy incidents for technical and non-technical stakeholders
Excellent judgment and the ability to collaborate with team members while navigating rapidly evolving priorities and workstreams
Preferred qualifications
Familiarity with credential-theft ecosystems or threat intelligence tooling
Experience working with fraud/risk vendors (e.g., device or network intelligence platforms)
Experience with API platform abuse specifically, not just consumer-account ATO
A deep interest in AI safety and responsible technology development
Experience writing effective prompts for generative AI systems in a content review or enforcement context
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary:
$245,000
—
$285,000 USD
Logistics
Minimum education:
Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study:
A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience:
Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy:
Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship:
We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification.
Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us.
To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit
anthropic.com/careers
directly for confirmed position openings.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage:
Learn about
our policy
for using AI in our application process.
San Francisco, CA | New York City, NY | Washington, DC
Location: San Francisco, CA | New York City, NY | Washington, DC
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the role
As a Safeguards Enforcement Analyst on the account abuse team, you'll build and execute enforcement workflows that keep our products safe, with a focus on detecting and mitigating potential harm. Your focus will be driving a number of enforcement areas including access controls and identity verification. You'll own the policy layer of these systems: what we ask users for, when, on what grounds, and what passes. The work sits at the intersection of policy, operations, and regulatory exposure.
This position may expand into broader areas of enforcement over time. Safety is core to our mission, and you'll help shape policy enforcement so that our users can safely interact with and build on top of our products in a harmless, helpful, and honest way.
Key responsibilities
Set collection policy for identity signals: what we request, in which enforcement states, and what evidence reinstates access
Improve verification program health — accuracy, appeal coverage, and consistency of outcomes
Own access policy for hard cases, including geographic restrictions and reseller arrangements
Run the operational queue for access-control cases alongside contractor support, authoring playbooks and QA'ing scaled review output
Work with Legal, Public Policy, and Privacy stakeholders to keep our approach proportionate, privacy-preserving, and responsive to an evolving regulatory landscape
Coordinate enforcement consistency with third-party platform partners
Keep up to date with emerging AI policy enforcement best practices, and use these to inform our decision-making and workflows
Stand up graduated enforcement in practice — verification requests, conditional reinstatement, and appeal pathways that satisfy regulatory requirements for automated decisions
Minimum qualifications
Experience in trust & safety, integrity, or risk policy work
Hands-on operational experience — you've owned or quality-checked live enforcement queues, not only authored policy
Subject matter expertise in one or more of: KYC, identity verification, age or identity assurance, or verification program operations
Experience navigating evolving regulatory landscapes (including frameworks like the DSA and GDPR) as design constraints rather than blockers
Experience driving cross-functional initiatives with Product, Engineering, Legal, and Policy partners — especially where safety, privacy, and usability tradeoffs need to be navigated together
Comfort using data (SQL or similar tools) to measure what's working and inform decisions
Strong written communication skills, with experience producing clear briefs and recommendations for technical and non-technical stakeholders
Excellent judgment and the ability to make consistent, defensible calls on ambiguous cases
Preferred qualifications
Experience with graduated/tiered enforcement systems rather than binary ban models
Experience with geographic access restrictions, sanctions screening, or reseller/channel policy
Experience building or scaling a contractor review bench
A deep interest in AI safety and responsible technology development
Experience writing effective prompts for generative AI systems in a content review or enforcement context
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary:
$285,000
—
$330,000 USD
Logistics
Minimum education:
Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study:
A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience:
Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy:
Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship:
We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification.
Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us.
To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit
anthropic.com/careers
directly for confirmed position openings.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage:
Learn about
our policy
for using AI in our application process.
Location: New York City, NY; San Francisco, CA
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the role
The Safeguards team is responsible for ensuring our models and products are developed and deployed safely. We're looking for engineers for our Review Tooling team, which builds the systems that humans — and increasingly Claude — use to investigate potential harms and take enforcement actions across Anthropic's first-party products and third-party cloud platforms.
You'll own the tools our safety investigators rely on to understand what's happening on our platforms and act on it, as well as the platform underneath those tools. That platform includes data analysis capabilities, privacy-preserving primitives that keep review workflows compatible with our data retention commitments, and a sandbox environment where new review interfaces and workflows can be built and iterated quickly.
These are internal tools, but they are anything but low-stakes: the speed, clarity, and reliability of this tooling directly determines how quickly Anthropic can identify harmful behavior, make sound enforcement decisions, and feed signals back into model training and safety classifiers. You'll partner closely with policy, operations, data science, legal, and privacy teams to ensure our enforcement systems are effective, accurate, and trustworthy.
Key responsibilities
Build investigation, review, and enforcement tooling for both first-party and third-party platform surfaces — including case queues, investigation views, decision and audit logging, and account-actioning workflows
Develop the platform layer of reusable APIs, data storage, and backend services that lets new review workflows be stood up quickly and safely
Stand up and run deployments of this tooling across multiple clouds, including inside cloud-provider partner environments where data must stay in place. Keep the deployments consistent through shared deployment pipelines, smoke tests, observability, and alerting
Scale review through automation, including enabling reviewers to use Claude effectively and building toward Claude-assisted and Claude-driven review workflows
Partner with policy, operations, legal, privacy, and data science stakeholders to translate enforcement and investigation needs into reliable, well-designed systems that measurably reduce handling time and decision error
Instrument the tools you ship — surfacing metrics on queue health, reviewer throughput, and decision quality — and ensure tooling evolves alongside new privacy primitives and data retention commitments
Minimum qualifications
A technical background in full-stack or platform engineering, with the ability to engage deeply in architecture and design discussions
Experience shipping internal tools or platforms with demanding operational users, and a track record of improving their workflows measurably
Experience working cross-functionally with non-engineering partners such as operations, policy, or legal teams
Excellent communication skills, including the ability to explain technical tradeoffs to non-technical stakeholders
Care about the societal impacts of AI and want your work to make powerful systems safer
Preferred qualifications
8+ years of industry software engineering experience
Experience building data labeling, trust and safety, integrity, fraud, or abuse-prevention tooling, or other systems supporting human review at scale
Have built systems that handle sensitive or regulated data, with requirements around access control, auditability, retention, and data residency
Have worked across multiple cloud providers, or built infrastructure designed to be provider-agnostic
A product-minded approach to internal users: you work directly with the people using your tools, watch where they struggle, and fix it
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary:
$320,000
—
$485,000 USD
Logistics
Minimum education:
Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study:
A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience:
Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy:
Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship:
We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification.
Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us.
To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit
anthropic.com/careers
directly for confirmed position openings.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage:
Learn about
our policy
for using AI in our application process.
Location: Baku
Workplace: onsite
ABOUT US
Xsolla is a global video game commerce company that provides a comprehensive suite of tools and services for game developers and publishers - including payments, distribution, game stores, launcher solutions, and partner network services. Our platform processes transactions across 200+ geographies, supporting thousands of games and millions of players worldwide. Quality is not optional - it is foundational to every product we ship.
ROLE OVERVIEW
The Director of QA is a senior technical leadership role responsible for owning and scaling Xsolla's quality engineering function across multiple product lines, teams, and time zones. You will define and drive the strategic vision for quality assurance - from test automation architecture and CI/CD integration to AI-assisted testing practices and performance engineering. You will lead a distributed organization of 30+ QA engineers and leads as part of a broader QA organization of 75+ professionals, ensuring predictable, high-quality releases across every product Xsolla delivers. This is not a management-only position. You must be deeply technical - capable of reviewing automation code, architecting test frameworks, debugging CI/CD pipelines, and evaluating AI-driven testing approaches hands-on.
Key Responsibilities
Strategic Leadership & Ownership
Define and execute the QA strategy across all Xsolla products, aligning quality objectives with business goals and product roadmaps.
Own QA deliverables end-to-end - from test planning through release sign-off - and be accountable for outcomes, not just activities.
Establish and enforce quality gates, defect governance policies, and release readiness criteria across all product teams.
Drive organizational maturity: evolve the QA function from reactive testing to proactive quality engineering embedded in every stage of the
SDLC
.
Represent QA at the executive level - articulate quality risks, tradeoffs, and resource needs to VP/C-level stakeholders with clarity and data.
Technical Excellence
Architect and oversee enterprise-grade test automation frameworks spanning UI (Playwright), API, database validation (SQL), and performance testing (K6).
Define and maintain standards for test code quality - including code reviews,
PR
contributions, reusable libraries, and modular test design.
Deep understanding of
Git workflows
- branching strategies, merge request reviews, repository hygiene, and code versioning best practices across multiple repositories.
Expert-level knowledge of
CI/CD pipelines
- design, optimize, and troubleshoot automated build, test, and deployment pipelines (GitHub Actions, GitLab CI, Jenkins, or similar).
Ensure all automation is fully integrated into CI/CD pipelines, with clear pass/fail signals, automated regression gates, and performance benchmarks at every release stage.
Drive adoption of
infrastructure-as-code
practices for test environments - containerized test execution, ephemeral environments, and environment parity between staging and production.
Evaluate, select, and implement QA tooling - including test management platforms (Qase), observability tools, and defect tracking integrations.
AI Integration & Innovation
Proven track record of using AI in day-to-day QA activities
- not aspirational, but demonstrated. You have used AI tools to generate test cases, write automation code, analyze test results, identify flaky tests, or accelerate debugging.
Champion and operationalize AI-assisted quality engineering across the organization - specifically using
Claude AI
for code generation, test design, automation scripting, and documentation.
Define governance frameworks for AI-generated test artifacts - validation, review, and sign-off processes to ensure AI outputs meet quality standards.
Stay current with AI/ML advancements relevant to testing - intelligent test selection, predictive defect analysis, autonomous test generation, and self-healing automation.
Establish metrics to measure the impact of AI adoption on QA velocity, coverage, and defect detection rates.
Team Leadership & People Development
Lead, mentor, and develop a distributed team of
30+ QA professionals
- including QA Leads, Senior QA Engineers, and QA Engineers - across
multiple time zones
(Americas, Europe, Asia-Pacific).
Build a high-performance culture rooted in ownership, technical excellence, continuous learning, and psychological safety.
Conduct regular 1:1s, career development conversations, and performance reviews. Identify and grow future QA leaders.
Design and implement onboarding programs, skill development paths, and technical training curricula - including AI literacy for all QA team members.
Manage resource allocation and capacity planning across multiple concurrent projects, ensuring predictable and sustainable QA delivery.
Navigate cross-cultural team dynamics with sensitivity and effectiveness - a truly global team requires a global leadership mindset.
Process Rigor & Quality Governance
Enforce rigorous QA processes across the organization: •
Test case management
: Create, maintain, and execute comprehensive test cases in
Qase
with full traceability (pass, fail, blocked statuses).
Bug documentation
: Ensure all staging bugs are filed with detailed reproduction steps, expected vs. actual behavior, environment details, screenshots/videos, and severity classification - following established training standards.
Automation framework documentation
: Maintain clear, up-to-date documentation for all automation frameworks, ensuring any engineer can onboard and contribute.
QA Score
: Drive iterative improvements in QA Score metrics - tracking automation coverage, defect escape rate, test execution velocity, and regression stability.
Define and track QA KPIs and OKRs - present quality dashboards and trend analysis to leadership regularly.
Conduct root cause analysis on production escapes and implement systemic corrective actions.
Cross-Functional Collaboration
Partner closely with Engineering, Product, DevOps, and Release Management to embed quality practices into every phase of the development lifecycle.
Work effectively in
Agile/Scrum environments
- participate in and drive sprint planning, retrospectives, daily stand-ups, and release ceremonies.
Act as the primary QA stakeholder for cross-functional initiatives - environment strategy, deployment automation, incident response, and post-mortem processes.
Build strong relationships with engineering leadership to ensure QA is not a bottleneck but an accelerator.
Common Expectations Across All QA Roles
Must be
technical and able to write code
for testing and automation.
Use
Claude AI
to assist in code creation, automation, and test design.
Follow QA processes rigorously: create and execute robust test cases in
Qase
, maintain clear documentation in automation frameworks, ensure traceability of executed test cases with statuses (pass, fail, blocked), and file
Staging Bugs
with detailed documentation following training standards.
Contribute to iterative improvements in QA Score and testing processes.
Strong communication and collaboration skills, analytical mindset, and commitment to continuous learning.
Ability to work effectively in Agile/Scrum environments, participating in sprint planning, retrospectives, and daily stand-ups.
Required Qualifications
15+ years of experience in QA/Quality Engineering
, with at least
6+ years in Senior Manager or Director-level roles
.
Proven experience leading teams of 30+ people
distributed across multiple time zones and cultural contexts.
Hands-on technical proficiency
- you can write and review test automation code, not just manage people who do. Proficiency in one or more: Python, JavaScript/TypeScript, Java.
Deep expertise in test automation frameworks
: Playwright, Selenium, Cypress, or equivalent for UI; REST/GraphQL API testing tools; database validation via SQL.
Performance testing experience
: K6, JMeter, Gatling, or Locust - designing, executing, and analyzing load/stress/soak tests.
Expert knowledge of Git
: branching strategies (GitFlow, trunk-based), pull request workflows, code review practices, repository management across multiple repos.
Expert knowledge of CI/CD
: designing and maintaining pipelines (GitHub Actions, GitLab CI, Jenkins, CircleCI), integrating automated tests into build/deploy workflows, debugging pipeline failures.
Demonstrated use of AI tools in professional QA work
- Claude, ChatGPT, Copilot, or similar - for test generation, automation coding, defect analysis, or process optimization. Provide specific examples.
Strong understanding of Agile/Scrum methodologies
and experience operating within and across Agile teams.
Experience with test management platforms
(Qase, TestRail, Zephyr, or similar).
Excellent communication skills
- ability to present complex technical quality topics to non-technical stakeholders, write clear documentation, and influence without authority.
Bachelor's degree in Computer Science, Engineering, or related field
(or equivalent practical experience).
Preferred Qualifications
Experience in the
video game, fintech, or e-commerce/payments industry
- understanding the unique quality challenges of high-throughput transaction systems.
Experience with
cloud-native architectures
(GCP, AWS, Azure) and testing strategies for microservices, event-driven systems, and distributed architectures.
Familiarity with
containerization and orchestration
(Docker, Kubernetes) for test environment management.
Experience building or managing
unified test environments
- non-production environment strategies that enable safe, deterministic, and scalable validation.
Knowledge of
security testing
fundamentals (
OWASP
, penetration testing, vulnerability scanning).
Experience with
data pipeline testing
and data quality validation.
Background in establishing
QA Centers of Excellence
or transforming QA organizations from manual-heavy to automation-first.
What Success Looks Like (First 12 Months)
90 days
: Complete assessment of current QA processes, tooling, team capabilities, and automation coverage. Establish relationships with all QA leads and key engineering stakeholders. Identify top 3 strategic gaps.
180 days
: Deliver a QA strategy roadmap aligned with product and engineering priorities. Implement measurable improvements in automation coverage and CI/CD test integration. Launch AI-assisted testing pilot across at least 2 product teams.
365 days
: Achieve measurable reduction in production defect escape rate. Demonstrate >80% automation coverage on critical regression paths. AI-assisted testing practices adopted across all QA teams. QA Score trending consistently upward. Team engagement and retention metrics at or above company benchmarks.
The duties and responsibilities of this position may evolve over time to support the organization’s goals and individual growth. This job description is intended to outline the general nature and level of work being performed and is not intended to be an exhaustive list of all duties, responsibilities, and qualifications required. By submitting your application, you consent to Xsolla conducting background checks, where permitted by law, after the final interview stage. All checks will comply with local regulations, and your information will be handled confidentially. Xsolla takes your privacy seriously and will not sell or externally distribute any personal data received during the hiring process. In accordance with applicable data protection laws, Xsolla is committed to protecting your personal information and respecting your privacy.
For any inquiries related to data privacy, please contact: careers@xsolla.com
Explore more opportunities at: https://xsolla.com/careers
Location: Mexico
You
Are passionate about technology, wake up every morning to experiment, learn and develop new solutions!
You Will
Work on latest edge Cloud computing to solve difficult, manual and repeatable tasks for users adopting Cloud technologies like AWS, Salesforce, Microsoft and more
Use the latest trends on building SaaS applications using multitenancy, scalability large data volumes / Big Data and more
Develop and expand our portfolio to support most popular Cloud apps (200+)
Develop understanding of not just software development, but also how to design, develop and launch a product from concept to high customer use.
About Us
At DBSync we provide opportunity to use technology that creates innovative and next generation data integration products which helps our employees to cultivate their creativity and sense of belonging. DBSync is a leading provider for data integration and Data warehousing services for both cloud/SAAS-based-on-demand applications. We were incubated by Salesforce.com (as a part of Avankia), before getting spunned off as a separate company. DBSync provides data integration as a SAAS-based, Standalone or hosted integration at a competitive price with a plethora of benefits for business users.
Our main motto is to provide a strong foundation for businesses in solving complex problems and automating their workflows while acting as a pillar of support for all their data integrations needs. At DBSync we encourage innovation and creativity and our team is diverse comprising of a nice mix of cultural blends. We are a family where each talent is recognised and honed for the best of the individual and the company as a whole. We maintain a very professional, learn and excel vision with a hint of a start-up-like environment making each individual feel important and responsible with an equal opportunity to grow to the sky’s limit!
If you have a spirit of enthusiasm to grow beyond horizons, a determination to work hard, confidence to achieve success and influence future visions and products and be a successful part of the next gen trend, DBSync is the place for you!
Our Value System
We genuinely care
We do not waste time on manual or mundane task
We have a fun environment
We own it
We are experts on what we do
We win together
DBSync has been:
We have been rated 4.7 / 5 on G2. We have got around 125 reviews in 2023.
Based on the reviews G2 has awarded DBSync following badges.
- Best Relationship- Winter 2024
- Leader Americas Winter 2024
- Best Results - Winter 2024
- Best Usability - Winter 2024
About the Role
The Forward Deployment Engineer (FDE) is a hybrid role at the intersection of engineering, business analysis, and customer success. Acting as the bridge between product teams and enterprise clients, FDEs ensure smooth deployment of AI-driven solutions, workflow automation, and SaaS integrations. They combine technical expertise with business acumen to translate client needs into production-ready solutions that drive measurable impact.
Roles and Responsibilities
Customer Discovery: Conduct structured workshops with client stakeholders to capture workflows, pain points, and desired outcomes.
Solution Design: Translate business requirements into technical workflows, automations, and integrations.
Deployment Execution: Configure, test, and deploy solutions, ensuring seamless go-live and adoption.
Workflow Automation: Build and customize automations using APIs, scripts, or low-code platforms.
Technical Troubleshooting: Diagnose integration issues, resolve blockers, and iterate based on client feedback.
Customer Advocacy: Serve as the technical expert during onboarding and beyond, ensuring long-term customer success.
Feedback Loop: Provide insights from deployments to product and engineering teams to shape roadmap priorities.
Skills and Qualifications
Bachelor's degree in Computer Science, Engineering, or related field — or equivalent demonstrated experience shipping production integrations.
4–8 years in a customer-facing technical role where you personally wrote and owned the code (Forward Deployed Engineer, Solutions Engineer, Integration Engineer, Implementation Engineer, or similar).
Strong coding ability (Python, Java, Go, or similar) — able to build and debug real integration logic, not just configure a UI.
Deep familiarity with SaaS systems, REST/SOAP APIs, webhooks, and authentication patterns (OAuth, API keys, SSO basics).
Experience with workflow automation platforms, CI/CD, and basic observability/monitoring tools.
Comfortable with SQL and at least one BI tool (Looker, Tableau, Superset) for validating data and demonstrating impact.
Demonstrated ability to operate independently in ambiguous, loosely-scoped situations and drive to a working solution.
Excellent communication skills — able to run a discovery workshop, explain a technical trade-off to a non-technical stakeholder, and write clear documentation.
Strongly Preferred
Hands-on experience with LLM/agentic frameworks (LangChain, LangGraph, CrewAI, or similar) and applying them to real workflow or data problems.
Experience with RAG pipelines, prompt/eval design, or AI observability and guardrails.
Prior experience embedded on-site with enterprise clients during implementation.
Nice to Have
Background in consulting or early-stage startup environments (frequently correlates with FDE success due to comfort with ambiguity and ownership).
MBA preferred.
Location:
Mexico (Remote, LATAM region)
Shift Timings:
U.S. Shift (8:00 AM CST - 5:00 PM CST)
For more information about DBSync, visit
www.mydbsync.com.
Video:
https://www.youtube.com/playlist?list=PLJzycdoERLoekPWNkXEsuih807TQAEnnB
Requirements
Benefits
Location: Remote, Canada; Remote, US
GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster.
The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems.
Co-create the future with us
as we build technology that transforms how the world develops software.
*
Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab.
An overview of this role
Site Reliability Engineers keep GitLab's user-facing services and production systems running reliably at scale. They combine software engineering with operational excellence, applying sound engineering principles, automation, and continuous improvement to build, operate, and evolve our production infrastructure.
This is a single application for Site Reliability Engineering opportunities across Infrastructure Platforms. Rather than asking you to choose the right team or level upfront, we evaluate your skills holistically and match you to the opportunity that best aligns with your experience and our hiring needs. We hire Site Reliability Engineers from Intermediate through Senior Staff across multiple Infrastructure Platforms teams.
We don't expect every candidate to have experience with every technology in our environment. We're looking for engineers with strong technical fundamentals, a growth mindset, and the ability to learn quickly. We'll support you in becoming successful with GitLab's tools, systems, and ways of working.
Please note: This position is open to candidates based in the United States and Canada only. Candidates based in the United Kingdom can apply to this posting:
Site Reliability Engineer, Infrastructure Platforms — UK (Intermediate to Senior Staff)
How our SRE hiring works
Because this is a single application for SRE roles across Infrastructure Platforms, our process is built to evaluate you once and match you well, rather than interviewing separately for every team.
Recruiter Screen:
A conversation about your background, what you're looking for, and the level and teams that fit, so we can point your process in the right direction.
Core Technical:
The shared assessment every SRE candidate takes, regardless of eventual team. A low-stress, collaborative discussion covering system architecture and incident review.
Hiring Manager Interview:
A conversation about ownership, judgment, execution, collaboration, and growth, the non-technical signals that make an SRE effective at GitLab.
Peer Technical:
Team-specific depth, run by SREs from the team you're most likely to join, focused on the problems that team actually works on.
Skip-Level Interview:
A conversation with a senior leader on values alignment, and how you'll work across teams.
After your interviews, we consider your performance alongside our current hiring needs to confirm the level and team where you'll do your best work. Interview results are a major factor, and final placement also reflects our active hiring priorities at the time.
We’ll calibrate your level throughout the interview process based on the scope and impact of your experience.
Intermediate: You independently deliver meaningful reliability improvements within a defined area.
Senior: You own complex reliability work end to end and raise the effectiveness of your team.
Staff: You shape reliability across multiple teams, solving systemic problems and creating approaches others can reuse.
Senior Staff: You set technical direction across a broader Infrastructure area and influence reliability strategy at organizational scale.
What you'll do
Keep user-facing services and production systems reliable, scalable, and efficient
Build automation and tooling that reduces toil and replaces manual work with repeatable, infrastructure-as-code-driven workflows
Operate and troubleshoot production systems on Kubernetes, including deployments, rollouts, and scaling
Write and maintain infrastructure as code, and ship changes safely through CI/CD and GitOps
Participate in on-call, triage alerts, follow and improve runbooks, and escalate appropriately
Contribute to the observability stack, using metrics, logs, and SLOs to detect symptoms early rather than just outages
Take part in incident response and post-incident reviews, turning learnings into changes in automation and process
Document runbooks, architecture decisions, and reviews so your findings become repeatable practices
What you'll bring
Experience keeping production systems reliable, combining an operations mindset with real software engineering practice
Experience building net-new infrastructure tooling and automation, not just configuring existing tools. For example, Terraform modules, Kubernetes operators or controllers, or production automation and services written from scratch
The ability to read, debug, and reason about code. Most of our teams work in Go; some work in Ruby. You can discuss a piece of code's behavior, performance, and failure modes
Experience with infrastructure as code, and with Kubernetes and its ecosystem, at a depth appropriate to your level
Hands-on experience with at least one major cloud provider (GCP or AWS)
Familiarity with observability practices, including metrics, logging, alerting, and SLOs or SLIs, and using data to inform operational decisions
Comfort participating in on-call and incident response, with a structured approach to troubleshooting under pressure
Strong written communication and the ability to operate as a manager-of-one in an async, distributed environment
A track record of using automation, and increasingly AI, to reduce toil and improve how you and your team work
Alignment with GitLab's values and a commitment to working in accordance with them
About the team
Infrastructure Platforms
is responsible for the availability, reliability, performance, and scalability of GitLab’s user-facing services, most notably
GitLab.com
. The organization spans teams across
Production Engineering
,
GitLab Dedicated
,
GitLab Delivery
, and
Developer Experience
, covering everything from the production fleet and networking platform to observability, incident response, deployment infrastructure, tenant scale, and our single-tenant Dedicated offering.
We are a globally distributed, remote-first organization that works asynchronously, favors automation over toil, and uses monitoring, metrics, and clear ownership to continuously improve the reliability of GitLab at scale. For more on how we work, see the
Infrastructure Handbook Page
.
The base salary range for this role’s listed level is currently for residents of the United States only. This range is intended to reflect the role's base salary rate in locations throughout the US. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, alignment with market data, and geographic location. The base salary range does not include any bonuses, equity, or benefits. See more information on our
benefits
and
equity
. Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary.
United States Salary Range
$126,400
—
$314,400 USD
How GitLab Supports Full-Time Employees
Benefits to support your health, finances, and well-being
Flexible Paid Time Off
Team Member Resource Groups
Equity Compensation & Employee Stock Purchase Plan
Growth and Development Fund
Parental Leave
Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from
underrepresented groups
are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application.
Country Hiring Guidelines:
GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process.
Privacy Policy:
Please review our
Recruitment Privacy Policy.
Your privacy is important to us.
GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also
GitLab’s EEO Policy
and
EEO is the Law
. If you have a disability or special need that requires
accommodation
, please let us know during the
recruiting process
.
Location: San Francisco, CA | New York City, NY | Washington, DC
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the role
As an Enforcement Analyst focused on Bio Harms, you will play a critical role in protecting against the misuse of AI systems for biological and related CBRNE harms. You will enforce our Usage Policy with a specific focus on detecting and mitigating bio risks, investigating potential violations, and help continuously strengthen our safeguards. The work sits at the intersection of biosecurity threat analysis and platform enforcement: you will read real model interactions and make fast, well-reasoned calls about whether activity is benign research or a credible attempt at harm.
This role is a fit for someone who understands the dual-use nature of biology and enabling technologies well enough to separate the benign from the malicious. You will own and continuously improve the enforcement monitoring workflows for the bio-harms area, and you will work closely with Policy, Threat Intelligence, Data Science, and Engineering cross-functional partners to accomplish tasks at scale. Safety is core to our mission, and your work will directly protect individuals, communities, and critical systems.
Important context for the role: In this position you may be exposed to and engage with explicit content spanning a range of topics, including material of a sexual, violent, or psychologically disturbing nature. The role also carries a shared on-call responsibility across the Policy and Enforcement teams.
Key responsibilities
Enforce Usage Policies with a specific focus on detecting and mitigating potential bio risks and harmful use of AI systems.
Take ownership of enforcement monitoring workflows for the bio-harms area, improving end-to-end detection, investigation, triage, and escalation processes.
Monitor and analyze platform activity to identify emerging patterns related to biological (and adjacent chemical, radiological, nuclear, and explosive) threats that may require policy updates or enforcement action.
Design and architect automated enforcement systems and review workflows that scale effectively while maintaining high accuracy across a technically complex content surface.
Conduct thorough investigations of potential violations, gathering and documenting evidence to support enforcement decisions.
Proactively surface trends and propose improvements to detection methods and review workflows.
Partner with Engineering and Data Science teams to optimize detection models and automated enforcement systems for bio-related policy violations.
Partner with Policy and Threat Intelligence groups to understand potential exploits and contribute to risk-assessment frameworks, and partner with engineers iterating on safety systems.
Provide enforcement-grounded feedback on policy gaps, and handle escalations and time-sensitive situations related to potential bio-related Usage Policy violations.
Minimum qualifications
Hold a degree in a bio-related field (e.g., microbiology, molecular biology, biochemistry, public health) and/or relevant professional experience in a related field.
Possess experience in Trust & Safety, content moderation, or policy enforcement at platform scale, including working with generative AI tools to refine and optimize content review and enforcement workflows.
Possess experience in utilizing AI tools to develop data dashboards for metrics collection in support of continuous improvement efforts.
Can analyze complex, ambiguous situations and make well-reasoned, defensible decisions under time pressure.
Are proactive and self-directed: you spot trends, dig in, and ship improvements on your own initiative.
Communicate clearly in writing and can translate technical bio concepts for diverse audiences, including both technical and non-technical stakeholders.
Preferred qualifications
Subject matter expertise in biodefense, biosecurity, WMD/CBRNE non-proliferation, or threat-intelligence.
An understanding of where real-world biological risk actually lies — adversary intent, acquisition and weaponization pathways, and dual-use concerns, including familiarity with cross-platform threat analysis and open-source intelligence (OSINT) techniques relevant to weapons of mass destruction.
Proficiency in SQL and/or other data analysis tools to draw insights from large datasets and monitor enforcement workflow health.
Familiarity with dual-use research of concern (DURC), select agents, and relevant policy frameworks.
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary:
$245,000
—
$285,000 USD
Logistics
Minimum education:
Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study:
A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience:
Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy:
Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship:
We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification.
Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us.
To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit
anthropic.com/careers
directly for confirmed position openings.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage:
Learn about
our policy
for using AI in our application process.
Location: San Francisco, CA | New York City, NY | Washington, DC
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the role
As an Enforcement Analyst focused on Chem & Explosives Harms, you will play a critical role in protecting against the misuse of AI systems for chemical and explosives harms. You will enforce our Usage Policy with a specific focus on detecting and mitigating these risks, investigating potential violations, and help continuously strengthen our safeguards. The work sits at the intersection of chemical and explosives threat analysis and platform enforcement: you will read real model interactions and make fast, well-reasoned calls about whether activity is benign research or a credible attempt at harm.
This role is a fit for someone who understands the dual-use nature of chemistry and explosives technologies well enough to separate the benign from the malicious — and who acts decisively under ambiguity. You will own and continuously improve the enforcement monitoring workflows for this harm area, and you will work closely with Policy, Threat Intelligence, Data Science, and Engineering matrix partners to accomplish tasks at scale. Safety is core to our mission, and your work will directly protect individuals, communities, and critical systems from AI-facilitated weapons harm.
Important context for the role: In this position you may be exposed to and engage with explicit content spanning a range of topics, including material of a sexual, violent, or psychologically disturbing nature. The role also carries a shared on-call responsibility across the Policy and Enforcement teams.
Key responsibilities
Enforce Usage Policies with a specific focus on detecting and mitigating potential chemical and explosives risks and harmful use of AI systems.
Take ownership of enforcement monitoring workflows for the chemical and explosives harm area, improving end-to-end detection, investigation, triage, and escalation processes.
Monitor and analyze platform activity to identify emerging patterns related to chemical and explosives threats (within the broader CBRNE landscape) that may require policy updates or enforcement action.
Design and architect automated enforcement systems and review workflows that scale effectively while maintaining high accuracy across a technically complex content surface.
Conduct thorough investigations of potential violations, gathering and documenting evidence to support enforcement decisions.
Proactively surface trends and propose improvements to detection methods and review workflows without waiting to be directed.
Partner with Engineering and Data Science teams to optimize detection models and automated enforcement systems for policy violations.
Partner with Policy and Threat Intelligence teams to understand potential exploits and contribute to risk-assessment frameworks, and partner with engineers iterating on safety systems.
Provide enforcement-grounded feedback on policy gaps, and handle escalations and time-sensitive situations related to chemical and explosives policy violations.
Minimum qualifications
Hold a degree in a chemistry-related field (e.g., chemistry, chemical engineering, materials science) and/or relevant professional experience in a related field.
Possess experience in Trust & Safety, content moderation, or policy enforcement at platform scale, including working with generative AI tools to refine and optimize content review and enforcement workflows.
Possess experience in utilizing AI tools to develop data dashboards for metrics collection in support of continuous improvement efforts.
Can analyze complex, ambiguous situations and make well-reasoned, defensible decisions under time pressure.
Are proactive and self-directed: you spot trends, dig in, and ship improvements on your own initiative.
Communicate clearly in writing and can translate technical chemistry concepts for diverse audiences, including both technical and non-technical stakeholders.
Preferred qualifications
Subject matter expertise in chemical and explosives defense, security, WMD/CBRNE non-proliferation, or threat-intelligence.
An understanding of where real-world chemical and explosives risk actually lies — adversary intent, acquisition and weaponization pathways, and dual-use concerns, including familiarity with cross-platform threat analysis and open-source intelligence (OSINT) techniques relevant to weapons of mass destruction.
Proficiency in SQL and/or other data analysis tools to draw insights from large datasets and monitor enforcement workflow health.
Familiarity with the Chemical Weapons Convention (CWC), scheduled chemicals, precursor controls, and energetic-materials safety frameworks.
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary:
$245,000
—
$285,000 USD
Logistics
Minimum education:
Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study:
A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience:
Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy:
Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship:
We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification.
Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us.
To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit
anthropic.com/careers
directly for confirmed position openings.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage:
Learn about
our policy
for using AI in our application process.
Location: San Francisco, CA | New York City, NY | Seattle, WA
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the role
The Claude Platform ships fast, and every launch lands better when the field can understand it, demo it, and teach it.
You'll own platform enablement end to end: the demos, hands-on labs, and technical curriculum that let Anthropic's go-to-market teams showcase the Claude Developer Platform with confidence, whether they're building on Anthropic's first-party API or through Bedrock, Vertex, and Foundry. You'll join roadmap and launch planning with the product team before features ship, so the field has what it needs on day one.
You're an engineer who teaches. You've shipped products to users. You know the difference between a demo that raises awareness and one that creates champions. And you get as much energy from watching a seller nail your lab as from building it yourself.
Key responsibilities
Turn launches into field-ready content:
Translate new platform capabilities (API, tool use and MCP, Agent SDK, memory and skills) into demos, labs, and quick-reference guides within days of release, and build compelling demo scenarios across industries and developer personas
Deliver training that sticks:
Run Claude Platform training for technical onboarding and ongoing enablement programs, delivering hands-on sessions wherever the field gathers, from a 12-person lab to a 100-person field-readiness day
Coach the field:
Coach technical sellers on demo delivery through practice sessions and office hours
Scale beyond the live session:
Develop self-service resources and experimental tools so the field can learn without you in the room, and contribute to the tooling that scales enablement, including demo environments, content-freshness automation, and self-service infrastructure
Close the loop with product:
Stress-test new platform features before launch, then bring field signal back to product and product marketing on where sellers get stuck and what content would unlock the next deal
Measure what lands:
Track content usage and session feedback so you know what is working and what to retire
Minimum requirements
Experience in a customer-facing technical role, such as solutions architecture, sales engineering, developer relations, or technical enablement
Experience writing production-quality code and building technical demos
Hands-on experience building with LLM APIs and agents, including tool use, MCP, or agent frameworks, beyond prompting alone
Experience using AI coding tools as part of your daily engineering work
Experience delivering live technical training or talks to both technical and non-technical audiences
Experience partnering directly with sales, solutions engineering, or other go-to-market teams
Preferred requirements
A portfolio you can show us: labs, courses, talks, or repos you built yourself
Experience with Claude Code, or a comparable agentic coding tool, as core infrastructure in your daily work
Experience building on the Claude Developer Platform through cloud providers such as Amazon Bedrock, Google Vertex AI, or Microsoft Foundry
Experience as a technical founder, early startup employee, or 0-to-1 operator who has taken an idea to product-market fit
Public speaking, conference presentations, or community-facing developer advocacy
Experience building enablement tooling, such as demo environments, content-freshness automation, or self-service infrastructure
Deep enthusiasm for AI and genuine care about building it responsibly
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary:
$290,000
—
$365,000 USD
Logistics
Minimum education:
Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study:
A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience:
Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy:
Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship:
We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification.
Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us.
To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit
anthropic.com/careers
directly for confirmed position openings.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage:
Learn about
our policy
for using AI in our application process.
Location: San Francisco, CA | New York City, NY | Washington, DC
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the role
As a Safeguards Enforcement Analyst on the user well-being team, you'll build and execute enforcement workflows that keep our products safe, with a focus on detecting and mitigating potential harm. Your initial focus will be on how Anthropic handles age. A core part of this work is making sure our consumer products reach the right audiences, including the detection signals, verification paths, and appeals workflows that keep underage users off surfaces not designed for them. Claude also reaches younger users through third-party developers building on our API, and you'll be the enforcement partner that sales and platform teams rely on when those customers need guidance on deploying age-appropriately.
This position may expand into broader areas of user well-being enforcement over time. Safety is core to our mission, and you'll help shape policy enforcement so that our users can safely interact with and build on top of our products in a harmless, helpful, and honest way.
Important context for this role: In this position you may be exposed to and engage with explicit content spanning a range of topics, including those of a sexual, violent, or psychologically disturbing nature. There is also an on-call responsibility across the Policy and Enforcement teams.
Key responsibilities
Design and architect automated enforcement systems and review workflows that scale effectively while maintaining high accuracy
Partner with Engineering and Data Science teams to optimize detection models for policy violations and automated enforcement systems
Review flagged content to drive enforcement and policy improvements
Enforce usage policies with a focus on detecting and mitigating potential harmful use of AI systems
Work with Legal, Public Policy, and Privacy stakeholders to keep our age assurance approach proportionate, privacy-preserving, and responsive to an evolving regulatory landscape
Support the Safeguards policy design team by providing detailed feedback on policy gaps based on real enforcement scenarios
Keep up to date with emerging AI policy enforcement best practices, and use these to inform our decision-making and workflows
Responsible for Anthropic's layered age assurance approach - self-declaration, behavioral signals, verification, and ban appeals - to keep our first-party consumer products safe
Adjacent user well-being enforcement where age is a key factor in how policy is applied such as sexual content and illicit substances
Minimum qualifications
Experience in trust and safety, online child safety, age assurance, privacy, product policy, or a related field
Subject matter expertise in one or more of: age assurance or age verification systems, age-appropriate design, child online safety, privacy-preserving verification methods, or content classification for young people
Experience driving cross-functional initiatives with Product, Engineering, Legal, and Policy partners — especially where safety, privacy, and usability tradeoffs need to be navigated together
Experience navigating evolving regulatory landscapes and enforcement best practices with regards to age assurance (including frameworks like the UK AADC, COPPA, and the DSA), CSAM/CSEM, NCII, and digital well-being
A thoughtful perspective on the privacy/safety tradeoffs inherent in age verification — including when less invasive approaches are the right call
Strong written communication skills, with experience producing clear briefs and recommendations for technical and non-technical stakeholders
Comfort using data (SQL or similar tools) to measure what's working and inform decisions
Excellent judgment and the ability to collaborate with team members while navigating rapidly evolving priorities and workstreams
Preferred qualifications
Experience building or operating age-gating flows, age estimation signals, underage account detection, or appeals workflows
Experience advising or partnering with third-party platforms on deploying safely to younger users
Experience working with or evaluating third-party age verification providers
A deep interest in AI safety and responsible technology development
Experience writing effective prompts for generative AI systems in a content review or enforcement context
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary:
$245,000
—
$285,000 USD
Logistics
Minimum education:
Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study:
A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience:
Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy:
Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship:
We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification.
Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us.
To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit
anthropic.com/careers
directly for confirmed position openings.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage:
Learn about
our policy
for using AI in our application process.
Location: Palo Alto; New York; San Francisco
Workplace: Hybrid
ABOUT MISTRAL
Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms.
We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited.
The Role
Mistral AI is seeking a Applied AI Engineer to facilitate the adoption of its products among customers and collaborate with them to address complex technical challenges.
The Applied AI Engineer will be an integral part of our Applied AI Engineering team, which is dedicated to driving the successful deployment of Mistral AI products. They will work hand-in-hand with customers from the pre-sale stage to post-implementation, ensuring our solutions meet and exceed client expectations.
In this role, you’ll manage daily customer relations involving multiple stakeholders (CEO/CTO, data scientists, and software engineers) and function as a key resource in externalising our research in production settings.
What You Will Do
• You’ll be responsible for onboarding customers on our products and APIs, providing guidance on prompting, evaluation, and fine-tuning, and ensuring the best production integration with back-end and front-end interfaces.
• You’ll work on state-of-the-art GenAI applications from consumer products to industrial use cases, driving with our customers a crucial technological transformation.
• You’ll individually help deploy into production use cases with a considerable business impact across various industries.
• You’ll work in collaboration with our researchers, other AI engineers, product engineers on our most complex customer projects involving complex fine-tuning, state-of-the-art LLM applications, and contributing to our open source codebases for tasks such as inference and fine-tuning.
• You’ll be involved in pre-sales calls to understand potential clients' needs, challenges, and aspirations. You will provide technical guidance on our products and explain Mistral technologies to various stakeholders.
• Your collaboration with our product and science team to improve continuously our product and model capabilities based on customers’ feedback
What We're Looking For
• You are fluent in English
• You hold a PhD / master in AI / data science.
• You have 2+ years as a technical individual contributor (data scientist or software engineer) on AI-based products
• You have experience in Fine Tuning LLMs, tackling advanced RAG or agentic use cases
• You have deep understanding of concepts and algorithms underlying machine learning and LLMs
• You're experienced with building and deploying LLMs or NLP applications
• You have proven experience in AI or machine learning product implementation with APIs, back-end and front-end interfaces.
• You have strong technical coding skills in Python
• You have experience with deep learning with Pytorch
• You have experience with agents framework such as Langchain, vector DBs
• You hold strong communication skills with an ability to explain complex technical concepts in simple terms with technical and non-technical audiences
Ideally you have:
• Contributed to open-source projects in particular in the space of LLMs
• Experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect or Technical Product Manager
WHAT WE OFFER
We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks.
For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link.
PRIVACY POLICY
Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.
Location: United States
Workplace: Remote
At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀
JOB SUMMARY
As a Support Automation Engineer on the Post Sales Systems team, you will design, build, and maintain the automation and AI systems that power ClickUp's post-sales support organization. You'll be responsible for translating business workflows in Zendesk and related CX platforms into scalable, intelligent automations that reduce manual effort, improve customer experience, and free up our support team to focus on high-value interactions.
This role sits at the intersection of engineering rigor and customer empathy. You'll partner closely with the Support and Success organizations, GTM Systems Leadership, and cross-functional stakeholders to automate away toil, surface insights through AI, and build systems that adapt to how support teams actually work. The kind of person who thrives here moves fast, takes full ownership of what they build, and is genuinely excited about applying AI to real operational problems. This role is a direct contributor to GTMSOE's broader mission of operational excellence across the GTM org.
KEY RESPONSIBILITIES
AI-POWERED AUTOMATION DESIGN & DEVELOPMENT
- Design and build automations in Zendesk that reduce repetitive support work: ticket routing, field population, note summarization, escalation logic, and customer outreach workflows.
- Develop AI-driven workflows using Zendesk AI, custom LLM integrations, and ClickUp Super Agents to automate tasks like ticket summarization, sentiment analysis, knowledge base matching, and response suggestions.
- Architect low-code/no-code automation solutions using Workato, Zapier, and similar integration platforms to connect Zendesk with Salesforce, ClickUp, Maven chatbot, and other tools.
- Own the full lifecycle of an automation: discovery, design, build, testing, deployment, and ongoing optimization based on usage and feedback.
CX SYSTEMS INTEGRATION & DATA FLOW
- Ensure seamless data flow between Zendesk, Salesforce, ClickUp, Chili Piper, Maven AGI chatbot, and other tools in the support tech stack.
- Design integration patterns that keep data clean, up-to-date, and accessible to downstream systems without creating maintenance nightmares.
- Build and maintain reporting dashboards and data pipelines that surface support health, automation impact, and team productivity metrics.
- Partner with the Support org to identify pain points, bottlenecks, and opportunities where AI and automation can deliver measurable value.
AI CAPABILITY EXPANSION
- Experiment with emerging AI/LLM capabilities (agents, RAG, fine-tuning) and determine which are production-ready for support workflows.
- Build reusable AI templates and patterns that other CX Systems team members can leverage, promoting consistency and reducing duplication.
- Collaborate with the broader GTM Systems Engineering team to share learnings and align on AI strategy across post-sales, sales, and finance domains.
- Log AI/automation work in the team's AI Excellence registry to promote transparency and cross-team learning.
RELIABILITY & CONTINUOUS IMPROVEMENT
- Monitor automation health, error rates, and SLAs; proactively identify and resolve issues before they impact support operations.
- Gather feedback from support teams and stakeholders; iterate on existing automations to improve accuracy, reduce false positives, and adapt to evolving business needs.
- Maintain documentation and runbooks so that support and CX teams understand how automations work and when to escalate issues.
- Help simplify and modernize existing architecture in Zendesk and connecting systems to improve long-term maintainability.
CROSS-FUNCTIONAL COLLABORATION
- Work closely with GTM Support teammates and leadership on intake, prioritization, and task execution.
- Partner with the Support and Success organizations and key stakeholders to translate business requirements into technical specifications.
- Contribute to the GTM Systems Engineering operating model: maintain task hygiene and communicate proactively on large initiatives.
QUALIFICATIONS
EXPERIENCE
- 3–5+ years in systems administration, business systems engineering, or customer support platform work.
- Demonstrated experience building automations or integrations that have shipped to production and delivered measurable business value.
- Hands-on experience with CX platforms, particularly Zendesk at an admin level or higher.
- Experience in a high-velocity, collaborative environment where you wear multiple hats and adapt quickly.
- Optional but valued: experience with ClickUp, Maven/chatbots, GTM systems, or support-focused SaaS operations.
SKILLS & COMPETENCIES
Technical
- Zendesk expertise: Hands-on experience with automations, triggers, business rules, and configuration (admin-level proficiency or higher).
- Integration & API work: Comfortable with REST APIs, webhooks, and integration platforms (Retool, Workato, Zapier, or similar low-code tools).
- AI & LLMs: Familiarity with prompt engineering, LLM APIs (OpenAI, Claude, etc.), MCP, and how to safely integrate AI into production workflows. You don't need to be an ML engineer, but you should understand when and how to apply AI to solve real problems.
- Data & scripting: Comfortable working with JSON, SQL, or light scripting (Python, JavaScript) to build data pipelines and transform data between systems.
- Salesforce integration: Understanding of Zendesk-to-Salesforce sync workflows, object relationships, and common integration patterns.
Operational & Mindset
- Ownership: You take full responsibility for the systems you build—reliability, documentation, and continuous improvement included. You don't hand off and walk away.
- Velocity: You move fast, iterate, and ship. You embrace "done is better than perfect" when appropriate, but never at the expense of reliability or customer trust.
- AI & Automation mindset: You're excited about LLMs and AI agents, not intimidated. You experiment, learn quickly, and know when to apply new tools and when to stick with what works.
- Collaboration: You're a skilled communicator who can translate between technical and non-technical stakeholders. You ask clarifying questions, challenge assumptions respectfully, and build trust with the teams you support.
- Growth: You're customer-centric and measure success not just by automation coverage, but by the real impact on support efficiency and quality.
WHAT YOU'LL WORK WITH
- Zendesk: Primary CX platform—automations, triggers, custom fields, custom apps, and reporting.
- ClickUp Super Agents: AI-powered automation and task orchestration within the ClickUp ecosystem.
- Salesforce: Zendesk-to-Salesforce integration, data sync, field mapping, and cross-system workflows.
- Integration stack: Workato, Zapier, and possibly Retool for custom apps and workflow orchestration.
- Maven chatbot & AI tools: In-app support, ticket automation, and AI-driven customer interactions.
- Data & reporting: ClickUp, Salesforce dashboards, and custom data pipelines for support metrics and insights.
Equal Opportunity Employer
ClickUp is an Equal Opportunity Employer, and qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin.
Privacy Notice
ClickUp collects and processes personal data in accordance with applicable data protection laws. You can find further details by viewing our Global Candidate Privacy Notice. https://clickup.com/careers-terms/candidate-privacy-notice
If you are a Philippine Job Applicant, please also see our Philippine Data Privacy Notice https://t333.s.clickup-attachments-stg.com/t333/d9a53ce2-6d2c-48cd-84b1-ed4e525f9613/Philippine%20Data%20Privacy%20Notice_2024.pdf?view=open for further details.
Visa Sponsorship
Please note we are unable to sponsor or take over sponsorship of an employment visa for roles outside of engineering and product at this time. Sponsorship for engineering and product roles is not guaranteed, but is instead based on the business needs for that specific role at that time. Please reach out to the recruiter with any questions.
Fraud Alert
ClickUp Talent Acquisition will only initiate contact via an @clickup.com http://clickup.com email or through our official careers portal on clickup.com http://clickup.com. We will never request fees, payments, or sensitive personal information. Please disregard any offers received outside these channels and report them to support@clickup.com.
AI Processing Notice
ClickUp may use artificial intelligence and machine learning technologies to help review and screen candidates' employment applications against role-related criteria. These tools support, but do not replace, human decision‑making. If you have questions or need an accommodation in the recruitment process, please contact us at AskPeople@ClickUp.com.
Location: San Francisco, CA | New York City, NY | Seattle, WA
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the role
The Fraud Prevention team protects Anthropic's payment and monetization surfaces from financial abuse — keeping fraud losses, dispute rates, and network monitoring exposure in check while preserving a smooth experience for legitimate customers. As a software engineer on this team, you will build the systems that make risk decisions in real time, manage the dispute and chargeback lifecycle, and detect monetization abuse across subscriptions, in-app purchases, and promotions. The ideal candidate can see things from attackers' perspectives, anticipate their responses to countermeasures, and never loses sight of the fact that a false positive here is a paying customer.
Payments fraud is more externally coupled than most trust and safety work — you'll collaborate closely with finance, support, and legal teams internally, and with payment processors and platform partners externally.
Responsibilities:
Design and build real-time risk decisioning that scores transactions at authorization time, balancing fraud loss, approval rates, and latency constraints
Build tooling and automation for the dispute and chargeback lifecycle, from review queues to evidence collection and loss reporting
Engineer fraud signals at scale — device fingerprinting, BIN and issuer signals, velocity features, and cross-account linkage — and detect monetization abuse across subscriptions, trials, promotions, and in-app purchases
Own a portfolio of metrics — loss rate, dispute rate, authorization approval impact, and false-positive rate — rather than optimizing any single number
Lead investigations into emerging fraud patterns, building multi-layered defenses designed for attacker adaptation rather than point-in-time rules
Work cross-functionally with finance, support, legal, and data science, and with external payment processors and platform partners
Minimum Qualifications:
Proficiency in Python, SQL, and data analysis tools
Experience building or operating fraud, risk, or abuse detection systems in production
Strong communication skills and ability to explain complex technical tradeoffs to non-technical stakeholders
Preferred Qualifications:
8+ years of industry software engineering experience, with a focus on payments fraud or risk
Fluency with payments rails: card networks, payment service providers (e.g., Stripe, Adyen), in-app purchase platforms (Apple, Google), refund flows, and the chargeback and dispute lifecycle
Direct experience combating fraud typologies such as card testing, stolen-card monetization, refund and chargeback abuse, subscription and trial abuse, promotional abuse, and friendly fraud
Understanding of fraud loss accounting — fraud loss vs. dispute fees vs. card network monitoring programs (e.g., VDMP, i VFMP, Mastercard ECP) — and why chargeback rate thresholds carry existential stakes
Experience building hybrid rules-and-ML risk systems: real-time scoring at authorization plus post-authorization review workflows
Experience at a marketplace or subscription business, or on a processor-side or issuer-side risk team
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary:
$320,000
—
$485,000 USD
Logistics
Minimum education:
Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study:
A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience:
Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy:
Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship:
We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification.
Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us.
To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit
anthropic.com/careers
directly for confirmed position openings.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage:
Learn about
our policy
for using AI in our application process.
Location: Palo Alto; New York; San Francisco
Workplace: Hybrid
ABOUT MISTRAL
Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms.
We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited.
Role Summary
As an AI Deployment Strategist, you will drive the adoption and deployment of Mistral’s AI solutions, working closely with customers from strategic vision to production implementation. This role sits at the intersection of business strategy, AI innovation, and hands-on deployment, ensuring our customers achieve transformative outcomes.
You will partner with senior executives to design AI roadmaps, collaborate with the Applied AI team to deliver solutions in production, and ensure seamless transitions from presales to postsales. Your work will directly contribute to customer success, bridging the gap between strategy and execution.
This role is ideal for those who thrive in a fast-paced environment, enjoy solving complex business challenges, and are passionate about turning AI potential into real-world impact.
What you will do
Strategic Discovery & Vision Setting
• Lead executive-level workshops to identify business challenges and opportunities where Mistral’s AI can drive step-change improvements.
• Co-create AI adoption roadmaps with customers, articulating the “art of the possible” and a clear path to value.
• Collaborate with Account Executives to develop business cases, quantify ROI, and align solutions with customer objectives.
AI Solution Design & Deployment
• Architect end-to-end AI solutions, integrating Mistral’s models and platform into customer workflows and technical infrastructure.
• Partner with the Applied AI team to design, prototype, and deploy AI solutions in production, ensuring scalability and impact.
• Own the execution of pilot projects and proofs-of-value, demonstrating the potential of our technology and paving the way for full-scale deployment.
Value Realization & Customer Success
• Serve as a trusted advisor to customers, guiding their AI strategy and ensuring they maximize the value of their investment in Mistral.
• Monitor key performance indicators (KPIs) tied to business outcomes, and communicate progress to executive sponsors.
• Proactively identify expansion opportunities within accounts, building on initial successes to drive long-term partnerships.
Cross-Functional Collaboration
• Act as the bridge between customers and Mistral’s internal teams, synthesizing feedback to influence product and research roadmaps.
• Develop reusable assets, best practices, and playbooks to scale go-to-market efforts and ensure consistent delivery excellence.
• Travel (~30-60%) to foster deep client relationships and support on-site deployment.
About you
• 4+ years in a client-facing strategic and technical role (e.g., data science consulting, value engineering, or technical sales).
• You hold a degree in a relevant scientific field (e.g., Computer Science, Data Science, Engineering, etc.)
• Foundational knowledge of AI/ML/Data Science, with the credibility to advise both technical and non-technical audiences.
• Hands-on experience building and deploying AI applications (Python, JavaScript, or similar) to demonstrate value.
• Strong business acumen and problem-solving skills, with the ability to structure ambiguous challenges into actionable solutions.
• Executive presence and communication skills to influence senior stakeholders (VP, C-level).
• Hands on experience building and deploying AI applications (Python)
• Resilient, results-driven, and comfortable leading through influence in a collaborative environment.
• Experience with sales qualification frameworks (e.g., MEDDPICC) and value-based selling is a plus.
Why This Role Matters You will play a pivotal role in shaping how enterprises adopt and deploy AI, ensuring Mistral’s solutions deliver measurable impact. By partnering with the Applied AI team, you’ll help turn strategic visions into production-ready solutions, making Mistral an indispensable partner for our customers.
WHAT WE OFFER
We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks.
For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link.
PRIVACY POLICY
Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.
Location: Mexico
Company Background
Our client is a global technology company transforming the way brands and agencies make marketing decisions. Its platform enables marketers to plan and activate cross-channel, programmatic media campaigns using real-time research, proprietary audience data, advanced analytics, and more than 150 integrated partners including Facebook, Instagram, Pinterest, Snapchat, and Twitter. The company operates across North America, Europe, the Middle East, Asia, and Australia.
Project Description
The role is focused on developing and modernizing real-time DSP serving services that process bid requests, deliver ads, integrate with third-party platforms, and record measurement events used for reporting and billing. The team works on high-throughput, low-latency systems processing millions of requests per second, with a strong focus on availability, data correctness, performance tuning, and scaling the platform for future growth. Current initiatives include splitting a monolith into microservices, improving deployment automation, and moving measurement pipelines from batch processing to real-time streaming with Kafka.
Technologies
Java
Kafka / Kinesis
Redis
S3
Tomcat
Docker, K8S
Git, CI/CD
What You'll Do
Develop critical high-performance, large-scale services for DSP programmatic integrations and platform products;
Work closely with the Product team to understand business needs and translate product requirements into technical solutions;
Write clean, efficient, and production-ready code with a strong focus on high throughput and low latency;
Design, develop, test, and improve new and existing platform features;
Contribute to building large-scale distributed systems processing billions of transactions per day under strict SLAs;
Improve test coverage, monitoring coverage, automation, and overall system observability;
Follow Agile methodologies and work in a fast-paced engineering environment with quick delivery cycles;
Job Requirements
5+ years of commercial experience in Java backend development, with a focus on scalable backend systems;
Strong knowledge of the JVM ecosystem, including garbage collection, profiling, and performance tuning;
Experience with distributed REST APIs, fault tolerance, scalability, consistency, and resilience;
Hands-on experience with low-latency and high-throughput services;
Experience with real-time streaming pipelines using Kafka, Kinesis, or similar technologies;
Strong knowledge of data structures and algorithms;
Experience with web/application servers such as Tomcat;
Solid understanding of networking and load balancing concepts;
Production experience with Docker and Kubernetes;
Experience with Git and CI/CD pipelines, such as GitLab CI/CD or similar tools;
Interest in applying modern technologies and AI-assisted development tools;
Readiness to participate in PagerDuty rotation (1 week per quarter);
Strong verbal and written communication skills, including the ability to explain complex technical trade-offs to both technical and non-technical stakeholders;
English: B2 or higher;
Nice To Have
Prior experience in the AdTech industry;
Familiarity with Python or Scala;
What Do We Offer
The global benefits package includes:
Technical and non-technical training for professional and personal growth;
Internal conferences and meetups to learn from industry experts;
Support and mentorship from an experienced employee to help you professional grow and development;
Health insurance;
Sports activities to promote a healthy lifestyle;
Flexible work options, including remote and hybrid opportunities;
Referral program for bringing in new talent;
Work anniversary program and additional vacation days.
Location: UK, London
Workplace: OnSite
Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further.
ABOUT THE ROLE
We're hiring a Senior or Staff Software Engineer to join our Data Engineering team based in London.
As the Data Platform Team, we strive to create the world’s leading, commercially scalable, safe, and advanced humanoid robots that seamlessly integrate into daily life and amplify human capacity.
We’re looking for experienced Engineers to help build our data platform from the ground up. You’ll have the opportunity to define its architecture, make key decisions, and shape how we handle and process petabyte-scale data in the near future.
WHAT YOU'LL DO
- Build the Capability Factory - an internal platform designed for everyone from software engineers to non-technical operators, enabling the entire organization to teach HMND robots new skills at scale, from raw data all the way to deployed capabilities.
- Curate, preprocess, and manage large-scale datasets for humanoid robot training - a corpus of robot telemetry growing toward petabyte scale.
- Design and operate highly scalable data pipelines and the compute infrastructure that powers them, ensuring reliability and throughput as data volume and team demands grow.
- Ensure the quality, accuracy, and consistency of training data across multiple concurrent projects and robot platforms.
- Collaborate with machine learning teams to shape the Capability Factory, streamline MLOps, and build the evaluation workflows that close the loop between training runs and real-world robot performance.
- Build data warehouse solutions and BI dashboards that give stakeholders across the organization clear visibility into data collection, model progress, and operational health.
- Establish and uphold best practices for data management - versioning, access control, security, and compliance.
WHAT WE'RE LOOKING FOR
- 5+ years of software engineering experience, with a track record of owning and delivering complex systems end-to-end, not just contributing to them.
- Strong backend engineering - designing and operating production-grade APIs and services: clean data modeling, reliable error handling, performance under load.
- Data engineering at PB+ scale - building and maintaining pipelines that move, transform, and validate large volumes of data reliably; understanding of batch and streaming processing patterns, data quality, and schema evolution.
- Workflow orchestration at scale - designing and operating multi-step automated pipelines with retries, observability, and graceful failure handling.
- Distributed systems fundamentals - you understand how things break at scale: eventual consistency, idempotency, backpressure, job scheduling, and failure modes in distributed compute and storage.
- Cloud infrastructure fluency - you have shipped and operated real systems on a major cloud provider; you think about cost, reliability, and security as first-class concerns, not afterthoughts.
- Container orchestration - deploying and operating workloads on Kubernetes at a level where you can debug scheduling issues, design resource allocation, and reason about cluster health without guidance.
- Full-stack range - comfortable building both the backend and the frontend of an internal product; you can own a feature from database schema to UI without handing off.
- Production ownership mindset - you've been on-call, triaged incidents under pressure, and improved systems after postmortems. You take reliability personally.
Nice to Have
- ML infrastructure or MLOps experience - understanding of how training jobs run, how model artifacts are managed, and what makes an evaluation pipeline trustworthy; you've worked alongside or directly supported ML researchers.
- Distributed compute frameworks - experience with large-scale parallel data processing, whether for data transformation, model training, or evaluation.
- Domain knowledge in robotics or embodied AI - familiarity with robot data formats, sensor telemetry, or the sim-to-real evaluation loop is a significant head start.
- BI and data warehouse experience - building data models and dashboards that translate raw operational data into decisions for non-technical stakeholders.
- Dual-cloud or multi-cloud storage - experience reasoning about cost, latency, and consistency tradeoffs across storage providers.
- Frontend product sense - beyond just shipping features, you have opinions about what makes an internal tool actually usable by non-engineers.
WHAT WE OFFER
- Competitive equity: stock options with meaningful upside as we scale.
- 30+ paid days off, including 23 days of annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown).
- Private healthcare, including virtual and in-person care.
- Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings.
- Free daily breakfast, catered lunch, and snacks in-office.
- Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics.
- Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.
Location: New York City Office
COMPANY DESCRIPTION
Today, when you go to your doctor and get referred to a specialist, your doctor sends out a referral and tells you, “They’ll be in touch soon.” So you wait. And wait. Sometimes days, weeks, or even months. Why? Because too often providers are overwhelmed with the painstakingly tedious work required to get paid by insurance companies. Powered by proprietary models, Tennr handles the complex paperwork that gets patients through the door and providers paid, helping operators get patients the right care, at the right time, in the right setting.
ROLE DESCRIPTION
As a Solutions Consultant at Tennr, your job is to walk into the messiest patient intake and authorization workflows in healthcare and prove, with evidence, not slides, that Tennr can fix them.
You get brought in once a deal is qualified and own the technical evaluation from first demo through signature. That means running discovery to uncover the real operational pain, translating it into a business case, and then building and delivering a proof of concept that makes the answer obvious. You'll partner closely with an Account Executive, but the evaluation is yours to win.
This is not a feature-demo role. The best SCs at Tennr understand the customer's business well enough to tell them something they didn't know about themselves — and then show them exactly how Tennr fixes it.
RESPONSIBILITIES
- Run structured discovery to identify operational pain points across referral intake, prior authorization, and patient processing workflows — and quantify what they're costing the organization.
- Deliver product demonstrations that are built around the prospect's specific problems, not generic feature walkthroughs.
- Architect and build tailored Proof of Concepts using Tennr's agentic patient orchestration platform, scoped to what will move the deal.
- Build current/future state process maps that make the before-and-after undeniable.
- Own deal strategy in partnership with the AE — know where the deal stands, who the stakeholders are, and what needs to happen to close.
- Become a genuine expert in the healthcare verticals you cover (DME, infusion, specialty pharmacy, home health) — understand the workflows, the payer dynamics, and the economics well enough to be credible in a room full of operators.
- Translate Tennr's technical capabilities into business outcomes for non-technical buyers (operations leaders, CFOs, clinical directors).
CANDIDATE QUALIFICATIONS
- 3-7 years in Solutions Consulting, Sales Engineering, or a technical customer-facing role at a B2B SaaS company.
- Technically hands-on — you've configured complex software platforms, worked with APIs, or built demo/sandbox environments without engineering doing it for you. You know how data moves through a system.
- Security and compliance fluency — you can read a SOC 2, interpret technical controls (encryption, access management, network segmentation), and respond to vendor security assessments without needing someone to translate for you.
- CS degree or equivalent technical foundation strongly preferred — not because we need you to write production code, but because it signals you can figure things out when the documentation runs out.
- Healthcare experience preferred — DME, infusion, specialty pharmacy, or any provider-side operations background is a significant plus.
- Comfortable presenting to and building credibility with both operational buyers and technical stakeholders (IT, security, compliance).
- Startup experience is a plus — you build process as you go and don't wait to be told what to do.
WHY TENNR?
- Drive Impact: one of our company values is Cowboy, meaning you set the pace. You won’t just talk about things, you’ll get them done. And feel the impact.
- Develop Operational Expertise: learn the inner workings of scaling systems, tools, and infrastructure.
- Innovate with Purpose: we’re not just doing this for fun (although we do have a lot of fun). At Tennr, you’ll join a high-caliber team maniacally focused on reducing patient delays across the U.S. healthcare system.
- Build Relationships: collaborate and connect with like-minded, driven individuals in our Hudson Square office 4 days/week.
- Free lunch! Plus a pantry full of snacks.
BENEFITS
- Beautiful new office at 345 Hudson Street
- Unlimited PTO
- 100% paid employee health benefit options
- Employer funded 401(k) match
- Competitive parental leave
Location: Bratislava, Slovakia
About Wolt
At Wolt, we create technology that brings joy, simplicity and earnings to the neighborhoods of the world. In 2014 we started with delivery of restaurant food. Now we’re building the delivery of (almost) everything and you’ll find us in over 500 cities in 30 countries around the world. In 2022 we joined forces with DoorDash and together we keep on dreaming big and expanding across the globe.
Working at Wolt isn’t always easy, but it’s definitely exciting. Here you’ll learn more, build more, and ship more than in most other companies. You’ll be challenged a lot, but also have a lot of fun on the way. So, if you’re a self-starter with drive and entrepreneurial spirit, this could be the ride of your life.
We kindly ask all candidates to submit a resume in English.
At Wolt, we’re building one of the most exciting media ecosystems in Europe - helping partners grow through Wolt Ads and Wolt Promos. By joining the team, you’ll be at the forefront of digital advertising, working on campaigns that drive visibility, engagement, and real results.
Our mission is to help partners grow their business by getting closer to the customers who matter most. Through high-impact placements across our app (and beyond), we help them boost brand visibility, reach new audiences, and increase sales.
As an
Ads & Promotions Sales Specialist
, you’ll work with our partners and help them utilise multiple Wolt tools - Wolt Ads & Wolt Promos. This role will be primarily responsible for selling Ads & Promos services to merchants, helping them identify the right advertising and promotional solutions to grow their business on Wolt. The person in this role will manage the full sales process, from merchant outreach and pitching to campaign setup coordination and post-campaign follow-up. They will also support ads & promos operations and reporting, ensuring that campaigns are launched on time, stay within budget, and that internal and external stakeholders receive clear performance insights. The ideal candidate will have basic sales experience, strong analytical skills, attention to detail, and a strong willingness to develop in Ads sales.
What you’ll be doing
Day-to-day in this role, you’ll:
Proactively contact our partners to secure their participation in Wolt Ads & Wolt Promotions campaigns.
Monitor campaign performance daily, analysing data and proactively identifying optimisation opportunities through performance dashboards.
Report performance and impact to both partners and internal stakeholders.
Set up and launch of ads and promos campaigns, ensuring accurate tracking and monitoring of delivery and performance.
Work with internal and external teams to ensure that campaigns are delivered on time and on budget.
Continuously identify opportunities to improve Ads & Promotions operations processes and procedures to increase efficiency and effectiveness.
Manage incoming queries regarding Wolt Ads & Wolt Promos.
Our humble expectations
If you have your first sales experience behind you, this is the role for you!
Excellent communication skills, both verbal and written, with the ability to communicate technical information to non-technical stakeholders.
Strong analytical skills with the ability to analyse and interpret data to inform decisions.
Strong attention to detail and ability to manage multiple projects simultaneously.
Ability to work independently and collaboratively with cross-functional teams in a fast-paced environment.
Fluency in Slovak and English.
What we offer
🌍 Independent work in a dynamic, international team.
💙 Employee Assistance Programme - therapy and wellbeing.
% Discount on your Wolt orders.
🤒 Sick days benefit.
💪 Sports benefit.
🚗 Fuel discount card.
💻 Modern work equipment.
Why you’ll love it
🚀 Global and growing fast: Be part of a fast-moving scale-up.
🤩 Ride of a lifetime: Accelerate your career and build your sales skills.
💪 Instant impact: Take ownership and make a difference.
💙 Big hearts and small egos: Surround yourself with smart, friendly people.
Next steps
If you are excited about working in a high-growth environment, taking ownership, and being part of an extremely ambitious team, then click below to apply, make sure to add your CV, and get the conversation going!
Curious about what goes on behind the scenes and want to learn more about the Ads & Promotions role? Dive into Roberta Poccafassi’s blog post to learn more:
here.
Wolt Ads is constantly expanding and evolving - check out how we help businesses grow and what opportunities lie ahead!
https://explore.wolt.com/en/fin/wolt-ads.
#LI-WM1
Compensation
The successful candidate's starting total target compensation (On-Target Earnings) for this role will fall within the pay range listed below and is determined based on a number of job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. This compensation is composed of a percentage based split between base salary and variable pay (where the base salary represents a percentage of the total range below. Eligible employees may earn variable compensation if they meet 100% of their performance targets. Actual earnings may be higher if targets are exceeded or lower if targets are not fully met.
Pay Range:
€1.700
—
€2.100 EUR
Our Commitment to Diversity and Inclusion
We’re committed to growing and empowering a more inclusive community within our company, industry, and cities. That’s why we hire and cultivate diverse teams of people from all backgrounds, experiences, and perspectives. We believe that true innovation happens when everyone has room at the table and the tools, resources, and opportunity to excel.
Beware of recruitment scams: DoorDash, Deliveroo, and Wolt will never ask you to pay money or share sensitive financial information during hiring — learn more about our legitimate recruiting process at
Recruitment Scam Awareness - DoorDash
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