Формирование единой системы HR-метрик и развитие сквозной аналитики процессов EJM от подбора до увольнения; Автоматизация C&B-отчетности и создание дашбордов для минимизации запросов на предоставление данных;
собирать, анализировать и документировать требования от внутренних и внешних заказчиков в Confluence. описывать методы для интеграций, разрабатывать функциональные спецификации и API-контракты совместно с ML- и backend-командами.
Location: Remote (Canada)
Workplace: Remote
BUILD SOMETHING PEOPLE LOVE
Wealthsimple is Canada’s leading financial innovator. The company offers a full suite of simple, sophisticated financial products across managed investing, do-it-yourself trading, cryptocurrency, tax filing, spending and saving. Wealthsimple currently serves more than 4 million Canadians and holds over $169 billion in assets under administration. The company was founded in 2014 by a team of financial experts and technology entrepreneurs, and is headquartered in Toronto, Canada.
We're proud of what we've built — and we're just getting started. Read our Culture Manual https://www.wealthsimple.com/en-ca/culture and learn more about how we work https://www.wealthsimple.com/en-ca/careers.
About the team:
At Wealthsimple, we aren't just managing portfolios; we're rewriting the rules of how Canadians interact with credit. The Credit Analytics team own’s Wealthsimple's lending ecosystem, operating at the intersection of high-growth tech and data-driven underwriting.
We believe that being “credit-worthy” should mean more than just a traditional score. Our mission is to challenge the status quo, building inclusive products that empower millions of Canadians and the businesses they run to lead better financial lives. We’re growing fast, moving from small data to massive scale through iteration and experimentation.
We are extending our consumer credit expertise into business lending built for Canadian small and medium-sized businesses (SMBs). This is a true green-field build — new adjudication policy, new underwriting signals, and new risk infrastructure, informed by everything we've learned scaling our consumer card portfolio.
About the role:
We are looking for a Senior Associate to own credit policy for our business lending products, starting with a business credit card — from adjudication through the full account lifecycle. You will design and implement the underwriting framework that determines who qualifies and at what limit, build the line management strategies that govern how those limits evolve, and partner closely with collections to manage risk once accounts are on book.
Small business cards can be underwritten on the owner, or on the business as it grows. You’ll be working with cash flow, seasonality, industry, and business bureau data, which is usually thinner and messier than consumer bureau data. We need someone who has worked across that range and can turn it into automated policy instead of file-by-file decisions.
You will collaborate cross-functionally with Engineering, Product, Data Science, Fraud, and Client Experience to translate policy into shippable adjudication and monitoring systems, and you will have significant ownership over how this portfolio’s risk appetite is defined from day one.
In this role, you will have the opportunity to:
- Build a new lending program from the ground up with the breadth to see every part of it, from policy to funding, and the runway to grow into leading a lending line of business.
- Design and own the adjudication policy for a new business credit card, including entity-level underwriting criteria, principal/guarantor assessment, joint-liability, initial limit-setting, and approval decisioning.
- Own line management strategy for business credit products: credit limit increases and decreases, pricing, authorization rules, and active exposure management driven by cash-flow and balance monitoring.
- Partner with the collections team to design risk-managed treatment strategies specific to business accounts, and to build lifecycle monitoring that catches emerging risk early.
- Evaluate the performance of the business lending portfolio and your policies, using vintage analysis, cohort tracking, and champion/challenger testing to validate and refine underwriting decisions.
- Propose policy enhancements that improve marginal profitability while keeping risk within appetite, informed by rigorous root-cause analysis rather than surface-level metrics.
- Help define the data and underwriting infrastructure needed for SMB lending — including how to source, validate, and weigh business financial data alongside traditional bureau signals.
- Influence roadmaps across partner teams (Engineering, Product, Data Science, Fraud, and Client Experience) and implement policy that drives measurable impact.
We're looking for someone who:
- Has direct experience underwriting or setting credit policy for small and medium-sized businesses, this is a must-have for this role. Card experience isn't required; we'd love to hear from you if your background is in instalment loans or lines of credit.
- Writes SQL hands-on to self-serve data and build monitoring and analytics.
- Brings credit discipline to a ship-and-iterate environment, and is comfortable shaping policy while the product itself is still being defined.
- Can turn analysis into a clear recommendation for technical and non-technical audiences, weigh incomplete or noisy information and still reach well-grounded decisions.
- Is intellectually curious, passionate about their work, and wants ownership over their projects.
Preferred qualifications:
- 5+ years of experience in small business lending
- Knowledge of Canadian consumer credit bureau data (Equifax, TransUnion)
- Working knowledge of how business credit risk differs from consumer credit risk: entity vs. personal guarantor assessment, business bureau data (e.g., business credit bureaus), cash-flow-based underwriting, industry/sector risk, and revenue seasonality.
- Experience across the credit lifecycle: adjudication policy, line management, pricing, and collections strategy.
- Experience with statistical/quantitative analysis: experimental design, champion/challenger (or A/B) testing, model accuracy validation, constrained optimization, decision trees, discounted cash flows, financial modeling.
- Experience with Python, and GitHub. Airflow, AWS Redshift, and dbt are a plus.
WHY WEALTHSIMPLE?
🌸 Top-tier health benefits and life insurance
📈 Long-term group savings with employer match, through Wealthsimple for Business
🌴 20 vacation days, 4 wellness days, and unlimited sick and mental health days per year*
✈️ 90 days away: work outside Canada for up to 90 days per year*
👥 Employee resource groups, including Rainbow (2SLGBTQ), Women of WS, and Black at WS
🌎 We are a hybrid team with over 1,500 employees across North America. The people are one of the best parts of working here: you'll collaborate with incredibly talented, curious, and driven teammates who are deeply committed to doing great work.
*Unlimited paid sick days, Wellness Days and the 90 day away program do not apply to certain roles.
ICYMI
Technology & Innovation at Wealthsimple: We move quickly and build thoughtfully. That means we're always looking for better ways to work — whether that's new tools, AI, or rethinking how we approach a problem. We don't expect you to have all the answers, but we do expect curiosity and a willingness to evolve alongside the products we're building.
Inclusion Statement: We're building products for a diverse world, and we need a diverse team to do it well. We strongly encourage applications from everyone, regardless of race, religion, colour, national origin, gender, sexual orientation, age, marital status, or disability status.
Accessibility Statement: We're committed to an accessible hiring experience. If you need any accommodations throughout the interview process, please let us know — we'll work with you to make sure you have what you need. We also welcome any feedback on how we can better accommodate candidates with accessibility needs.
AI in Hiring: We may use artificial intelligence (AI) tools to support parts of our hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our team but don't replace human judgment – all final hiring decisions are made by people. If you have questions about how your data is used, reach out to us.
Location: Remote, Maryland, United States; Remote, Massachusetts, United States, AMER; Remote, New Jersey, United States, AMER; Remote, New York, United States, AMER; Remote, Pennsylvania, United States, AMER; Remote, Virginia, United States, AMER; Remote, Washington DC, United States, AMER
From Fivetran’s founding until now, our mission has remained the same: to make access to data as simple and reliable as electricity. With Fivetran, customer data arrives in their warehouses, canonical and ready to query, with no engineering or maintenance required. We’re proud that more organizations continue to leverage our technology every day to become truly data-driven.
About Us
Fivetran and dbt Labs are bringing together two industry-leading companies with a shared mission: helping organizations unlock the full value of their data. Together, we’re delivering the data infrastructure layer that helps organizations move, transform, and trust their data — from the moment data moves, through every transformation, to the context teams and AI systems rely on.
Fivetran helps organizations automate data movement across the systems, clouds, engines, and tools they rely on. dbt Labs pioneered analytics engineering, helping teams transform data into reliable, governed insights.
Together, we support thousands of organizations as they build a trusted foundation for analytics, AI, and better business decisions. As we bring our teams and technology together, we’re building on the strengths of both companies while continuing to deliver the products and experiences our customers know and trust.
It’s an exciting time to join us: we’re creating a company with the scale, talent, and technology to help more organizations put their data to work with greater speed, confidence, and impact.
During this transition period, you may see references to both Fivetran and dbt Labs throughout our recruiting process as we integrate our teams, systems, and career sites.
About the Role
We’re seeking an experienced Sr. Technical Instructor with a passion for teaching and working with data to join our training team to setup Enterprise customers and partners for success with dbt to empower data developers to create and disseminate organisational knowledge.
What You’ll Do
Deliver live, world-class instruction to train and onboard dbt customers, partners, and GSIs in small (~10), large groups (up to ~30) and webinar audiences (50 - 200)
Create an engaging learning environment initially in a remote context (on Zoom!) and likely in person in the future
Get learners excited about using dbt to make an impact at their organization
Clearly teach and demo new concepts and skills for learners
Facilitate live co-development sessions where learners apply what they have learned
Adjust instruction on the fly while focusing on learner outcomes
Provide critical feedback from your classroom experience to improve curriculum changes
Become a product expert with dbt in the context of the modern data stack (if you aren’t already)
Jump in on other education projects including curriculum development and improving our workflows
Skills We’re Looking For
You have 4+ years experience teaching with some data analytics experience OR 4+ years of data analytics experience with some teaching
You have experience writing SQL in an analytics context
You love teaching and creating those lightbulb moments for learners
You create learning environments with high levels of engagement
You are laser focused on learner and customer outcomes while adjusting instruction on the fly - our customers are coming to use our product from varied tooling and skillsets
You believe teaching is a craft that we can always get better at and actively seek out feedback
You communicate clearly and concisely with internal and external stakeholders
You thrive in an environment of cross-collaboration that moves quickly
Bonus Skills
You have worked on customer education / training teams and know how training can drive outcomes for customers.
You have experience using dbt and/or teaching dbt.
You have experience writing analytics code (i.e. python, R, etc.) in addition to SQL and working with databases
You have experience designing curricula with a focus on backwards design.
The compensation range displayed on this job posting reflects the minimum and maximum target for new hire compensation for the target position and level, and may include sales incentives or target bonuses depending on the role. Our compensation ranges are determined by role, level, and location. Our job titles may span more than one career level. Within the range, individual compensation is determined by additional factors, including job-related skills, experience, relevant education or training, business need, market demands. The compensation range is subject to change and may be modified in the future. Your recruiter can share more about the specific compensation range for your location during the hiring process.
Pay Range
$112,842
—
$135,416 USD
Perks and Benefits
100% employer-paid medical insurance
*
Generous paid time away from work, including paid vacation or flexible/unlimited vacation depending on role and country, plus paid sick time, inclusive parental leave, paid holidays, including a year-end Global Week of Rest, and volunteer days off.
RSU stock grants*
Professional development and training opportunities
Company virtual happy hours, free food, and fun team-building activities
Monthly cell phone stipend
Access to an innovative mental health support platform that offers personalized care and resources in areas such as: therapy, coaching, and self-guided mindfulness exercises for all covered employees and their covered dependents.
*
May vary by country and worker type - please reach out to your recruiter for more information
Click
here
to learn more about Fivetran's Benefits by Region.
We’re honored to be
valued at over $5.6 billion
, but more importantly, we’re proud of our
core values of Get Stuck In, Do the Right Thing, and One Team, One Dream
. Read about us in
Forbes
.
Fivetran brings together high-quality talent across the globe to make data access as easy and reliable as electricity for our customers. We value and recognize that our customers benefit from having innovative teams made of people from many backgrounds, experiences, and identities. Fivetran promotes diversity, equity, inclusion & belonging through attracting, recruiting, developing, and retaining a diverse workforce, not only because it is the right thing to do, but because it helps us build a world-class company to better serve our customers, our people and our communities.
To learn more about Fivetran’s culture and what it’s like to be part of the team,
click here
and enjoy our video.
To learn more about our candidate privacy policy, you can
read our statement here
.
We are committed to ensuring that all candidates have an equal opportunity to participate in our interview process. If you require accommodations at any stage of the process due to a disability, medical condition, or any other circumstance, please don't hesitate to submit your request by filling out this
form
. We will work with you to provide reasonable accommodations to facilitate your participation and ensure a fair and accessible interview experience. Your request and any information provided will be kept confidential and will not impact your candidacy. We look forward to hearing from you and accommodating your needs to the best of our ability.
Location: New York, New York, United States
About the Role
The ideal candidate for this role is a strong cloud architect who excels at both big-picture thinking as well as hands-on technical work. With very strong AWS, Kubernetes and web infrastructure skillsets, they will be working on projects building or improving our core compute, core network and edge infrastructure. They also play a critical role in helping the iCapital platform scale and doing so with an automation-first mentality. The engineer will work with application and platform teams to onboard services, establish connectivity, troubleshoot traffic flows, and maintain consistent networking patterns across environments.
Responsibilities
Design and continually improve Kubernetes architecture, also helping operationally manage cluster lifecycle.
Work on projects integrating new self-hosted and SaaS services, in some cases understanding and working with developers to help design software architecture
Manage Transit Gateway, Network Firewall and external connectivity. Own architectural guidance for edge and traffic management, including CDN, DNS, and TLS strategies (e.g., Akamai, Cloudflare).
Produce and maintain reference architectures, design documents, and architectural guardrails
Partner with engineering, security, and product teams to ensure platform standards are practical, well understood, and broadly adopted.
Qualifications
8+ years of experience in platform, cloud, or infrastructure engineering roles, with demonstrated architectural responsibility. Must have strong hands-on experience designing and operating Kubernetes platforms in production environments, including a strong understanding of autoscaling strategies, node provisioning, and security on EKS.
Deep understanding of AWS infrastructure, including networking, security primitives, and managed services. This includes expertise in cloud networking architecture patterns, including VPC design, routing, and planning for scale.
Strong understanding of ingress/egress, TGW design and private connectivity.
Comfortable operating as a senior individual contributor with influence across multiple teams as a leader.
Very Strong written and verbal communication skills, with the ability to explain architectural decisions to both technical and nontechnical audiences.
Preferred Qualifications
Expertise in Kong or other API Gateways at a deep level
Experience directly managing Akamai in a production environment
Strong understanding of application design principles
Some experience with EKS standards such as Bottlerocket, Karpenter, Auto-mode
A software engineering background is helpful, and some experience with Python expected.
Certifications (AWS / Kubernetes) are a plus but not required.
Benefits
The base salary range for this role is $150,000 to $190,000 depending on level. iCapital offers a compensation package which includes salary, equity for all full-time employees, and an annual performance bonus. Employees also receive a comprehensive benefits package that includes an employer matched retirement plan, generously subsidized healthcare with 100% employer paid dental, vision, telemedicine, and virtual mental health counseling, parental leave, and unlimited paid time off (PTO).
We believe the best ideas and innovation happen when we are together. Employees in this role will work in the office Monday-Thursday, with the flexibility to work remotely on Friday.
For additional information on iCapital, please visit
https://www.icapitalnetwork.com/about-us
Twitter: @icapitalnetwork | LinkedIn:
https://www.linkedin.com/company/icapital-network-inc
| Awards Disclaimer:
https://www.icapitalnetwork.com/about-us/recognition/
iCapital is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender, sexual orientation, gender identity, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.
Location: Brazil
About the Role
Join Alvys, an early-stage company transforming the $800B US freight industry. As a DevSecOps Engineer, you'll help protect our platform and the customer data it holds. You'll close cloud security gaps, build security checks into how we ship software, run our penetration testing program, and stand up the infrastructure behind our internal security, IT, and AI tools. This role combines hands-on infrastructure work with coordination across DevOps, engineering teams, IT & Security, and outside security vendors.
Industry Insight
Freight companies run their business on Alvys: loads, drivers, carriers, payments, and financial records. As more of the industry moves to modern software, customers expect that data to be protected like any other business-critical system. Security is part of how we earn and keep their trust.
About Alvys
Alvys is building a multi-tenant SaaS platform that powers modern transportation operations. We combine deep industry knowledge with strong technical execution to bring clarity, automation, and reliability to one of the world's most essential industries. Security is a shared responsibility at Alvys, and this role helps every team meet that bar.
Our Principles
Engineering Principles
Build for Real-World Impact.
Our users rely on Alvys to solve real problems, not abstract ones. Every security fix should reduce real risk to our platform and the people moving freight every day, not just clear a scanner finding.
Extreme Ownership and Empowerment.
Ownership extends beyond building. It means being accountable for quality, reliability, and customer impact. If it's in production, it's yours: bugs, uptime, and results.
Technology Debt is Strategic, Not Accidental.
Technical debt is a strategic choice, not an oversight. We incur it deliberately when it unlocks speed, learning, or market advantage. Our architecture remains clean, maintainable, and scalable as we grow.
Simplicity Scales; Complexity Costs.
Logistics is inherently complex, but our technology shouldn't be. We prioritize simplicity in our architecture, leveraging modularity and well-defined service boundaries to reduce cognitive load.
Radical Transparency.
We democratize data and make it accessible across all functions to drive alignment and decision-making. Transparency also means feedback. We systematize constructive feedback loops to ensure growth.
Engineering Culture
Move Fast, Learn Fast.
Speed is our advantage, but we move fast intentionally. We bias for action, assume positive intent, and treat every mistake as a learning opportunity.
Own the Outcome.
Every engineer owns outcomes, not tickets. We take responsibility end-to-end, identifying problems, delivering solutions, and ensuring they last.
Partner, Don't Gatekeep.
Security works best when it's built with the teams who own the systems. We share context with DevOps and engineering teams, explain the risk behind each ask, and make the secure path the easy one.
Pragmatism Over Purism.
Perfect security doesn't exist, but reduced risk does. We choose fixes that scale, are maintainable, and address real threats, not theoretical ones.
People Over Heroics.
We don't reward burnout or always-on behavior. Sustainability is a feature, not a luxury. If someone needs to slow down, unplug, or take care of life outside work, that's expected.
Responsibilities
Cloud security architecture
Design and deliver infrastructure changes that strengthen our cloud security posture, including network isolation and identity-based access.
Make these changes through infrastructure as code, plan rollouts that avoid customer downtime, and work with service owners to update the applications that depend on them.
Build secure defaults into our infrastructure modules so new resources start out compliant.
Vulnerability management and pipeline security
Help run our vulnerability management program, driving remediation within defined SLAs.
Extend our existing security scanning with AI-assisted security testing, such as automated security code review and AI-driven penetration testing.
Tune and improve the automation we already use to process security findings.
Penetration testing
Manage our third-party penetration tests from start to finish: scoping and targeting, test environments and accounts, vendor coordination, findings intake, and retesting.
Help mature our internal, AI-assisted penetration testing tool into a dependable part of the security program, including deployment and scheduled runs.
Infrastructure for security, IT, and AI tooling
Deploy and operate internal applications in Azure, with identity, secrets, networking, and backups set up correctly from day one.
Build telemetry pipelines (OpenTelemetry into Azure Monitor) for our AI and internal tools, with dashboards and alerts that surface anomalous activity.
Working with others
Partner with DevOps, engineering teams, and IT & Security to plan and prioritize work.
Write clear runbooks and documentation, and produce evidence for our SOC 2 program.
Tech Stack
Cloud: Azure (AKS, App Service, Azure Functions, Storage, Key Vault, Cosmos DB, VNets, Microsoft Entra ID)
Infrastructure as code: Terraform
CI/CD: GitHub Actions and Azure DevOps pipelines
Containers: Docker, Kubernetes, Azure Container Registry
Observability: Azure Monitor, App Insights, Log Analytics, OpenTelemetry, Grafana
Security: Aikido, Cloudflare
AI tooling: Cursor, Claude, Claude Platform (managed agents), Grokbot
Application code: .NET/C#, TypeScript, Angular, React
Minimum Qualifications
Fluent in English, spoken and written.
3+ years of professional experience in DevOps, cloud infrastructure, platform engineering, or security engineering.
Hands-on experience with at least one major cloud provider (Azure, AWS, or GCP), including networking, identity and access management, and secrets management.
Production experience with infrastructure as code, preferably Terraform.
Experience building and maintaining CI/CD pipelines.
Working knowledge of containers and Kubernetes.
Scripting skills in Python, PowerShell, or Bash.
Understanding of common security risks in cloud and web applications, and how to fix them.
Ability to explain technical risk clearly to engineers and non-engineers.
Preferred Qualifications
Experience with Azure specifically, including private endpoints, VNet integration, and Entra ID managed identities.
Experience with application security testing (SCA, SAST, DAST), and interest in applying AI to security testing.
Experience coordinating penetration tests or working with external security firms.
Experience with OpenTelemetry, Azure Monitor, or similar observability tools, including writing alert queries (KQL is a plus).
Familiarity with SOC 2, ISO 27001, or CIS Benchmarks.
Interest in AI tooling and how to deploy and monitor it safely.
Security certifications such as AZ-500, Security+, or similar are a plus.
Background in logistics or transportation is a bonus.
Location: Mexico
About the Role
Join Alvys, an early-stage company transforming the $800B US freight industry. As a DevSecOps Engineer, you'll help protect our platform and the customer data it holds. You'll close cloud security gaps, build security checks into how we ship software, run our penetration testing program, and stand up the infrastructure behind our internal security, IT, and AI tools. This role combines hands-on infrastructure work with coordination across DevOps, engineering teams, IT & Security, and outside security vendors.
Industry Insight
Freight companies run their business on Alvys: loads, drivers, carriers, payments, and financial records. As more of the industry moves to modern software, customers expect that data to be protected like any other business-critical system. Security is part of how we earn and keep their trust.
About Alvys
Alvys is building a multi-tenant SaaS platform that powers modern transportation operations. We combine deep industry knowledge with strong technical execution to bring clarity, automation, and reliability to one of the world's most essential industries. Security is a shared responsibility at Alvys, and this role helps every team meet that bar.
Our Principles
Engineering Principles
Build for Real-World Impact.
Our users rely on Alvys to solve real problems, not abstract ones. Every security fix should reduce real risk to our platform and the people moving freight every day, not just clear a scanner finding.
Extreme Ownership and Empowerment.
Ownership extends beyond building. It means being accountable for quality, reliability, and customer impact. If it's in production, it's yours: bugs, uptime, and results.
Technology Debt is Strategic, Not Accidental.
Technical debt is a strategic choice, not an oversight. We incur it deliberately when it unlocks speed, learning, or market advantage. Our architecture remains clean, maintainable, and scalable as we grow.
Simplicity Scales; Complexity Costs.
Logistics is inherently complex, but our technology shouldn't be. We prioritize simplicity in our architecture, leveraging modularity and well-defined service boundaries to reduce cognitive load.
Radical Transparency.
We democratize data and make it accessible across all functions to drive alignment and decision-making. Transparency also means feedback. We systematize constructive feedback loops to ensure growth.
Engineering Culture
Move Fast, Learn Fast.
Speed is our advantage, but we move fast intentionally. We bias for action, assume positive intent, and treat every mistake as a learning opportunity.
Own the Outcome.
Every engineer owns outcomes, not tickets. We take responsibility end-to-end, identifying problems, delivering solutions, and ensuring they last.
Partner, Don't Gatekeep.
Security works best when it's built with the teams who own the systems. We share context with DevOps and engineering teams, explain the risk behind each ask, and make the secure path the easy one.
Pragmatism Over Purism.
Perfect security doesn't exist, but reduced risk does. We choose fixes that scale, are maintainable, and address real threats, not theoretical ones.
People Over Heroics.
We don't reward burnout or always-on behavior. Sustainability is a feature, not a luxury. If someone needs to slow down, unplug, or take care of life outside work, that's expected.
Responsibilities
Cloud security architecture
Design and deliver infrastructure changes that strengthen our cloud security posture, including network isolation and identity-based access.
Make these changes through infrastructure as code, plan rollouts that avoid customer downtime, and work with service owners to update the applications that depend on them.
Build secure defaults into our infrastructure modules so new resources start out compliant.
Vulnerability management and pipeline security
Help run our vulnerability management program, driving remediation within defined SLAs.
Extend our existing security scanning with AI-assisted security testing, such as automated security code review and AI-driven penetration testing.
Tune and improve the automation we already use to process security findings.
Penetration testing
Manage our third-party penetration tests from start to finish: scoping and targeting, test environments and accounts, vendor coordination, findings intake, and retesting.
Help mature our internal, AI-assisted penetration testing tool into a dependable part of the security program, including deployment and scheduled runs.
Infrastructure for security, IT, and AI tooling
Deploy and operate internal applications in Azure, with identity, secrets, networking, and backups set up correctly from day one.
Build telemetry pipelines (OpenTelemetry into Azure Monitor) for our AI and internal tools, with dashboards and alerts that surface anomalous activity.
Working with others
Partner with DevOps, engineering teams, and IT & Security to plan and prioritize work.
Write clear runbooks and documentation, and produce evidence for our SOC 2 program.
Tech Stack
Cloud: Azure (AKS, App Service, Azure Functions, Storage, Key Vault, Cosmos DB, VNets, Microsoft Entra ID)
Infrastructure as code: Terraform
CI/CD: GitHub Actions and Azure DevOps pipelines
Containers: Docker, Kubernetes, Azure Container Registry
Observability: Azure Monitor, App Insights, Log Analytics, OpenTelemetry, Grafana
Security: Aikido, Cloudflare
AI tooling: Cursor, Claude, Claude Platform (managed agents), Grokbot
Application code: .NET/C#, TypeScript, Angular, React
Minimum Qualifications
Fluent in English, spoken and written.
3+ years of professional experience in DevOps, cloud infrastructure, platform engineering, or security engineering.
Hands-on experience with at least one major cloud provider (Azure, AWS, or GCP), including networking, identity and access management, and secrets management.
Production experience with infrastructure as code, preferably Terraform.
Experience building and maintaining CI/CD pipelines.
Working knowledge of containers and Kubernetes.
Scripting skills in Python, PowerShell, or Bash.
Understanding of common security risks in cloud and web applications, and how to fix them.
Ability to explain technical risk clearly to engineers and non-engineers.
Preferred Qualifications
Experience with Azure specifically, including private endpoints, VNet integration, and Entra ID managed identities.
Experience with application security testing (SCA, SAST, DAST), and interest in applying AI to security testing.
Experience coordinating penetration tests or working with external security firms.
Experience with OpenTelemetry, Azure Monitor, or similar observability tools, including writing alert queries (KQL is a plus).
Familiarity with SOC 2, ISO 27001, or CIS Benchmarks.
Interest in AI tooling and how to deploy and monitor it safely.
Security certifications such as AZ-500, Security+, or similar are a plus.
Background in logistics or transportation is a bonus.
Location: United States
About the Role
Join Alvys, an early-stage company transforming the $800B US freight industry. As a DevSecOps Engineer, you'll help protect our platform and the customer data it holds. You'll close cloud security gaps, build security checks into how we ship software, run our penetration testing program, and stand up the infrastructure behind our internal security, IT, and AI tools. This role combines hands-on infrastructure work with coordination across DevOps, engineering teams, IT & Security, and outside security vendors.
Industry Insight
Freight companies run their business on Alvys: loads, drivers, carriers, payments, and financial records. As more of the industry moves to modern software, customers expect that data to be protected like any other business-critical system. Security is part of how we earn and keep their trust.
About Alvys
Alvys is building a multi-tenant SaaS platform that powers modern transportation operations. We combine deep industry knowledge with strong technical execution to bring clarity, automation, and reliability to one of the world's most essential industries. Security is a shared responsibility at Alvys, and this role helps every team meet that bar.
Our Principles
Engineering Principles
Build for Real-World Impact.
Our users rely on Alvys to solve real problems, not abstract ones. Every security fix should reduce real risk to our platform and the people moving freight every day, not just clear a scanner finding.
Extreme Ownership and Empowerment.
Ownership extends beyond building. It means being accountable for quality, reliability, and customer impact. If it's in production, it's yours: bugs, uptime, and results.
Technology Debt is Strategic, Not Accidental.
Technical debt is a strategic choice, not an oversight. We incur it deliberately when it unlocks speed, learning, or market advantage. Our architecture remains clean, maintainable, and scalable as we grow.
Simplicity Scales; Complexity Costs.
Logistics is inherently complex, but our technology shouldn't be. We prioritize simplicity in our architecture, leveraging modularity and well-defined service boundaries to reduce cognitive load.
Radical Transparency.
We democratize data and make it accessible across all functions to drive alignment and decision-making. Transparency also means feedback. We systematize constructive feedback loops to ensure growth.
Engineering Culture
Move Fast, Learn Fast.
Speed is our advantage, but we move fast intentionally. We bias for action, assume positive intent, and treat every mistake as a learning opportunity.
Own the Outcome.
Every engineer owns outcomes, not tickets. We take responsibility end-to-end, identifying problems, delivering solutions, and ensuring they last.
Partner, Don't Gatekeep.
Security works best when it's built with the teams who own the systems. We share context with DevOps and engineering teams, explain the risk behind each ask, and make the secure path the easy one.
Pragmatism Over Purism.
Perfect security doesn't exist, but reduced risk does. We choose fixes that scale, are maintainable, and address real threats, not theoretical ones.
People Over Heroics.
We don't reward burnout or always-on behavior. Sustainability is a feature, not a luxury. If someone needs to slow down, unplug, or take care of life outside work, that's expected.
Responsibilities
Cloud security architecture
Design and deliver infrastructure changes that strengthen our cloud security posture, including network isolation and identity-based access.
Make these changes through infrastructure as code, plan rollouts that avoid customer downtime, and work with service owners to update the applications that depend on them.
Build secure defaults into our infrastructure modules so new resources start out compliant.
Vulnerability management and pipeline security
Help run our vulnerability management program, driving remediation within defined SLAs.
Extend our existing security scanning with AI-assisted security testing, such as automated security code review and AI-driven penetration testing.
Tune and improve the automation we already use to process security findings.
Penetration testing
Manage our third-party penetration tests from start to finish: scoping and targeting, test environments and accounts, vendor coordination, findings intake, and retesting.
Help mature our internal, AI-assisted penetration testing tool into a dependable part of the security program, including deployment and scheduled runs.
Infrastructure for security, IT, and AI tooling
Deploy and operate internal applications in Azure, with identity, secrets, networking, and backups set up correctly from day one.
Build telemetry pipelines (OpenTelemetry into Azure Monitor) for our AI and internal tools, with dashboards and alerts that surface anomalous activity.
Working with others
Partner with DevOps, engineering teams, and IT & Security to plan and prioritize work.
Write clear runbooks and documentation, and produce evidence for our SOC 2 program.
Tech Stack
Cloud: Azure (AKS, App Service, Azure Functions, Storage, Key Vault, Cosmos DB, VNets, Microsoft Entra ID)
Infrastructure as code: Terraform
CI/CD: GitHub Actions and Azure DevOps pipelines
Containers: Docker, Kubernetes, Azure Container Registry
Observability: Azure Monitor, App Insights, Log Analytics, OpenTelemetry, Grafana
Security: Aikido, Cloudflare
AI tooling: Cursor, Claude, Claude Platform (managed agents), Grokbot
Application code: .NET/C#, TypeScript, Angular, React
Minimum Qualifications
Fluent in English, spoken and written.
3+ years of professional experience in DevOps, cloud infrastructure, platform engineering, or security engineering.
Hands-on experience with at least one major cloud provider (Azure, AWS, or GCP), including networking, identity and access management, and secrets management.
Production experience with infrastructure as code, preferably Terraform.
Experience building and maintaining CI/CD pipelines.
Working knowledge of containers and Kubernetes.
Scripting skills in Python, PowerShell, or Bash.
Understanding of common security risks in cloud and web applications, and how to fix them.
Ability to explain technical risk clearly to engineers and non-engineers.
Preferred Qualifications
Experience with Azure specifically, including private endpoints, VNet integration, and Entra ID managed identities.
Experience with application security testing (SCA, SAST, DAST), and interest in applying AI to security testing.
Experience coordinating penetration tests or working with external security firms.
Experience with OpenTelemetry, Azure Monitor, or similar observability tools, including writing alert queries (KQL is a plus).
Familiarity with SOC 2, ISO 27001, or CIS Benchmarks.
Interest in AI tooling and how to deploy and monitor it safely.
Security certifications such as AZ-500, Security+, or similar are a plus.
Background in logistics or transportation is a bonus.
Equal Employment Opportunity
Alvys is an equal opportunity employer and as such, we do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or any other characteristic protected by applicable laws.
We are dedicated to growing a diverse team of highly talented people. We’re dedicated to building a workplace where we give each other the strategies, support, and space we each need to thrive—believing in and bringing out the best of everyone.
If you require any accommodations during the recruitment process, whether it be alternate forms of material, accessible meeting rooms, etc., please let us know and we will work with you to meet your needs.
For information about Alvys's privacy practices, see our
Privacy Policy
.
Location: San Francisco, CA | 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
Anthropic is seeking an Accountant to join our Corporate Accounting team. You will be a hands-on member of the close: owning a defined set of accounts and entities from transaction through reconciliation, and making sure what lands in the financial statements is accurate, supported, and explainable.
This is a role for someone who likes getting into the detail and also asks why the process works the way it does. You will work closely with partners across Finance, Procurement, Payroll, Legal, Tax, and Finance Systems, and you will help us build a close that scales with the company, with a lot of room to improve how the work gets done as we grow.
Key responsibilities
Own month-end and quarter-end close activities for an assigned set of accounts and entities, including journal entries, accruals, account reconciliations, and supporting schedules, delivered on the close calendar
Prepare balance sheet reconciliations and flux analyses, investigate variances to root cause, and write clear explanations for reviewers and business partners
Maintain US GAAP supporting schedules and documentation for your areas of ownership, such as prepaids, fixed assets, accruals, and intercompany balances
Draft accounting memos and process documentation for routine and recurring transactions, and escalate non-routine items to Technical Accounting with a clear summary and a proposed treatment
Execute internal controls for your areas and prepare audit support, including schedules, evidence, and responses to auditor requests
Partner with business owners and finance colleagues to understand new transactions, resolve issues at the source, and reduce adjustments after close
Review work from contractors and team members, and give feedback that helps the team raise its quality bar
Identify and implement process improvements and automation, including using Claude and other AI tools, and check the output carefully before anyone relies on it
Support system and process changes in the accounting function, including testing, data validation, and documentation
Minimum qualifications
Working knowledge of US GAAP, applied hands-on to the monthly close: journal entries, accruals, reconciliations, and financial statement support
Experience preparing account reconciliations and flux analyses in an ERP or general ledger system (for example, Workday, NetSuite, or equivalent)
Strong spreadsheet skills, including lookups, pivot tables, and reconciling large data sets in Excel or Google Sheets
Experience supporting external audits and operating internal controls
Clear written and verbal communication, including the ability to explain accounting results to colleagues who are not accountants
Sound judgment on when to resolve an issue independently and when to escalate it
Attention to detail and a strong sense of ownership, with the ability to manage competing deadlines
Preferred qualifications
7+ years of progressive accounting experience, in public accounting, in industry, or a combination of both
CPA, ACA, ACCA, or CA qualification, or progress toward one
Experience in a fast-moving environment where processes were still being defined, with a track record of improving them
Familiarity with technical areas such as ASC 842, ASC 718, ASC 606, fixed assets, or multi-entity and intercompany accounting
Experience with close management or reconciliation tooling, or with SQL or Python for data analysis
Experience with an ERP migration, SOX readiness, or public company reporting
A track record of using AI tools to speed up accounting or finance work, with checks that hold up to review
Genuine interest in AI and Anthropic's mission to build reliable, interpretable, and steerable AI systems
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:
$160,000
—
$190,000 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; San Jose, CA; Seattle, WA
Workplace: Remote
ABOUT DOCKER
Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout.
We are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default.
_______________________________________________________________________
THE ROLE
Docker Forward Deployed Engineers (FDE) embed directly with our most strategic customers to solve important, complex technical problems and turn ambitious ideas into production outcomes. FDEs take on the most challenging technical challenges using existing Docker products and patterns when possible, and work across customer, Docker Product and Engineering teams to realize new approaches when required.
As a Docker FDE, you will work side-by-side with customer engineering teams to deeply understand their goals, problems, constraints, and technical landscape; identify the highest-leverage opportunities; and design, build, and ship solutions with them. You own the technical journey from discovery and architecture through prototyping, implementation and production rollout.
The solutions you build may use existing Docker products, extend Docker into new environments, integrate deeply with customer and third-party systems, or reveal capabilities that Docker should build next. You work closely with Docker Solutions Architects to evolve existing patterns, and Docker Product and Engineering to turn new learnings into reusable patterns and product capabilities.
_______________________________________________________________________
RESPONSIBILITIES
Build in Production with Customers
- Embed with customer engineering teams to design, build, and ship solutions from first prototype through stable production rollout. Use existing Docker products and patterns when possible, invent, prototype and validate innovative solutions when necessary.
- Deliver working technical artifacts to customers: custom MCP servers with tightly integrated Docker Sandbox environments for coding agents and containerized agents; Docker Compose definitions for multi-agent harnesses and model-backed applications; Hardened Image standardization and migration; New tools that unblock customer progress.
- Integrate Docker's AI platform with the customer's existing stack, including identity providers (OIDC/SAML/SSO), secrets management, private and air-gapped registries, Kubernetes, CI/CD pipelines, and observability tooling.
- Own technical delivery on your engagements: scope the work, sequence it, make trade-offs between speed and quality, remove blockers early, and contribute directly to code whenever progress depends on it.
Make AI Adoption Safe and Governable
- Translate customer security, compliance, and platform requirements into concrete plans and see those plans through from ideation to production.
- Help customers define controls to enable them to adopt agentic AI to solve their unique business problems without compromising security, compliance, data sovereignty or end-user experience.
- Establish quality and performance standards for customers and work closely with Docker Product and Engineering to quickly address issues that fall outside of established thresholds
- Partner with customer security and platform teams to get agentic workloads through architecture review, threat modeling, and change control.
Partner with Solutions Architecture and the Field
- Work closely with Solutions Architects to enable off-the-self solutions when possible and provide technical experience and leadership when a bespoke solution is necessary.
- Feed implementation learnings back into reference architectures, SOW templates, and success patterns so that FDE innovations become standard features and implementation patterns.
- Support the field with technical depth during proofs of concept, escalations, and expansion conversations when a working build is the fastest path to a customer adoption.
Close the Loop with Product and Engineering
- As part of Docker Engineering FDEs work closely with Product and Engineering teams to fold FDE innovations, learnings, and design patterns into existing or new products and services.
- Work with Customers, Product and Engineering to establish quality and performance thresholds, ensuring customer environments meet them consistently, and responding quickly and decisively when they don’t.
- Be the voice of the customer. Deliver data-driven and actionable feedback to Product and Engineering: what works well; what does not; what customers are asking for; and what blocks their adoption and forward progress. FDE experience directly influences the roadmap.
Shape the Practice
- Define the FDE engagement model, delivery standards, and quality bar, and codify them so that engagements are consistent across customers, regions, and delivery partners.
- Mentor and lead other Forward Deployed Engineers, and participate in hiring loops to grow the team.
- Act as the senior technical escalation point on the hardest problems impacting your customers. Every incident is an opportunity to improve Docker products and services.
- Maintain deep, current knowledge of the agentic AI stack: LLMs, APIs, MCP, coding agents, model and harness evaluation approaches, performance and quality thresholds, deployment patterns.
- This role may require participation in an on-call rotation to provide support outside of standard business hours, including evenings, weekends, and holidays, as needed.
_______________________________________________________________________
QUALIFICATIONS
Required
- 10+ years of software engineering experience, including 4+ years in a customer-facing technical role such as Forward Deployed Engineer, Solutions Engineer, Professional Services Engineer, or Software Engineer with consulting or technical founder experience.
- Technical leadership across multiple engagements, teams, or domains, with a proven ability to set delivery standards, define repeatable patterns, and influence product direction through field evidence.
- Expert production coding skills in Go, Python, or TypeScript, with a track record of shipping and operating software that other people depend on and of leading technical design reviews.
- Deep, hands-on Docker expertise: Dockerfiles and multi-stage builds, Docker Compose, image and registry operations, container networking and storage, and container security fundamentals.
- Hands-on experience building with LLMs and agents in production, including tool use and function calling, the Model Context Protocol (MCP server and client implementation), prompt and context engineering, and evaluation of agent behavior.
- Working knowledge of software supply chain security: SBOMs, image signing and attestation, vulnerability management, minimal and hardened base images, and secure CI/CD.
- Experience integrating with enterprise systems: identity providers (Okta, Entra ID, LDAP/Active Directory), federated identity protocols (OIDC, SAML), secrets managers, Kubernetes, and at least one major cloud platform (AWS, Azure, GCP).
- Ability to scope and deliver complex work in ambiguous, fast-moving customer environments, making sound trade-offs between scope, speed, and quality.
- Excellent communication skills with engineers, security and platform teams, and executive stakeholders, with a low-ego, collaborative approach and the ability to lead through influence rather than authority.
- Proven track record of technical mentorship and of raising the bar for the engineers around you.
- High agency and comfort operating autonomously in distributed, remote-first teams.
- Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
- Travel to customer sites to build in person with customer teams, estimated at up to 50%.
Bonus
- Experience with Docker Hardened Images, Docker Scout, MCP Gateway, MCP Toolkit, Docker Sandboxes, or Docker Model Runner.
- Experience deploying and operating coding agents (Claude Code, Codex, Gemini CLI, Cursor, or similar) in team or enterprise settings.
- Experience with air-gapped, regulated, or compliance-driven environments in financial services, healthcare, government, or similar sectors.
- Contributions to open source projects in the container, Kubernetes, or MCP ecosystems.
- Prior experience founding or scaling a Forward Deployed Engineering or Professional Services practice.
Visa sponsorship: Docker considers visa sponsorship on a case-by-case basis based on business needs.
_______________________________________________________________________
COMPENSATION & EQUITY
All full-time roles include equity. Final compensation is determined on factors including but not limited to experience, skills, qualifications, and location.
United States: $198K – $319K base
______________________________________________________________________
POSTING INFORMATION
- Open vacancy: This posting is for an existing open role.
- AI in hiring: Docker may use AI-assisted tools during our recruiting process.
- Interview recordings: Candidates will be invited to opt in to interview recordings to support interviewer calibration and consistent evaluations. Recordings are optional and require explicit consent.
______________________________________________________________________
PERKS & BENEFITS
- Remote-first by design – Work from your home, with offices in Seattle and Paris for connection and collaboration.
- Flexibility that fits your life – We trust you to manage your schedule while delivering great work.
- Time to recharge – Generous PTO, designated quarterly Whaleness Days, and a designated end-of-year Whaleness break.
- Home office support – Set up your workspace for comfort and success.
- Technology stipend – Equivalent to US$100 net per month to help support your work.
- Learning & development – Annual stipend for conferences, courses, certifications, and continued learning.
- Parental leave – 16 weeks of paid parental leave after six months of employment.
- Equity for all full-time employees – Share in Docker's long-term success as we continue to grow.
- Comprehensive benefits – Medical, retirement, and paid holidays vary by country.
- Docker swag – Because representing the whale never gets old.
Docker is proud to be an equal opportunity employer. We are committed to building a team that reflects a broad range of backgrounds, experiences, and perspectives. We believe diverse teams build better products, make better decisions, and better serve our global community.
#LI-REMOTE
Location: Tokyo, Japan
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 Regional Research Economist at Anthropic, you will collaborate with governments, academia, industry, and civil society in your region to measure and understand AI’s effects on the economy and explore research-driven policy interventions. You will contribute to the development of the Anthropic Economic Index and its extension to generate regionally relevant insights, establish new methodologies to measure the usage, diffusion, and impact of AI throughout the economy, and work to broaden access to and usage of the insights generated by the Index. You will use frontier methods in econometrics, machine learning, and structural estimation. Such rigor will drive impact, shaping both policy discussions externally and informing Anthropic’s internal business and product decisions.
Our team combines rigorous empirical methods with novel measurement approaches. We’re building first-of-its-kind datasets tracking AI’s impact on labor markets, productivity, and economic transformation. Using our privacy-preserving measurement system (
Clio
), we
analyze millions of real-world AI interactions
to understand how AI augments and automates work across different occupations and tasks.
For this role, we’re looking for candidates who can combine rigorous economic analysis with novel measurement approaches to understand AI’s transformative effects on the economy. The ideal candidate will be comfortable working at the intersection of empirical economics, technological change, and policy impact.
Key responsibilities
Build and maintain relationships with academic institutions, policy think tanks, and other research partners as the primary point of contact for these organizations on economic impact work in your region
Advance research collaborations that answer country- or regional-specific economic impact questions
Translate research insights into actionable recommendations for policy discussions
Make fundamental contributions to the development and expansion of the
Anthropic Economic Index
, including country- and regional-specific analysis
Design and collaborate on empirical research on AI’s economic effects with governments, academia, industry, and civil society in your region
Develop new methodological approaches, in collaboration with partners in your region, for studying AI’s impact on labor markets and the future of work; productivity and task transformation; economic inequality and displacement; industry-specific disruption and adaptation; and aggregate economic trajectories (GDP, productivity, unemployment) under varying AI-adoption scenarios
Work cross-functionally with other technical teams to improve our measurement infrastructure and data collection
Amplify external engagement through research publications, policy briefs, and presentations to diverse stakeholders
Minimum qualifications
PhD in Economics
Strong track record of empirical research, particularly studies combining novel data sources and economic theory or implementing frontier methods in causal inference and machine learning
Demonstrated experience working in, and relevant relationships across, the region
Proficiency in Python, R, SQL, or similar tools for large-scale data analysis
Demonstrated ability to lead complex research projects from conception to publication
Demonstrated ability to communicate technical findings to diverse audiences
Demonstrated ability to build relationships across academic, policy, and industry communities
Preferred qualifications
Experience relevant to the study of AI’s impact on the economy, such as labor market analysis and occupational change; task-based approaches to technological transformation; large-scale data analysis and econometric methods; large language models for social science research; policy-relevant economic research; experimental and quasi-experimental methods for causal inference; macroeconomic modeling and time series forecasting; or agent-based modeling and large-scale simulation
Experience working with novel datasets and measurement systems
Comfort learning new technical tools and frameworks
Strong interest in ensuring AI development benefits humanity
Comfort working with AI systems and ability to think critically about their capabilities and limitations
Representative projects
How Australia Uses Claude: Findings from the Anthropic Economic Index
Anthropic Economic Index Report: Economic Primitives
Anthropic Economic Index Report: Uneven Geographic and Enterprise AI Adoption
Estimating AI productivity gains from Claude conversations
The Anthropic Economic Index
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: United Kingdom; Bulgaria; Ukraine; Poland; Hungary; Czechia; Ireland
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. 🚀
The role
ClickUp's Cloud Platform team builds scalable, secure, and cost-efficient AWS infrastructure, with a heavy focus on Amazon EKS, that stays ahead of product and enterprise growth. Our goal: product velocity is never blocked by platform constraints. As a Senior Software Engineer, you leverage AI to design, build, and operate the compute, networking, and infrastructure-as-code foundation that powers ClickUp for millions of users.
What you'll do
- Build and scale AWS infrastructure and reusable platform abstractions that simplify development, with a strong focus on Amazon EKS, networking, and self-hosted services.
- Identify improvement opportunities and emerging risks, and propose novel solutions that improve reliability, scalability, and cost efficiency before constraints become blockers.
- Automate shard buildouts and implement Terraform guardrails and hardened ingress that reduce incidents.
- Scale systems for multi-shard, multi-region growth while meeting compliance attestations (SOC 2, ISO 27001, etc), disaster recovery, and enterprise security requirements.
- Partner with SRE, Security, product, AI, and enterprise teams to bridge infrastructure and product engineering.
- Own the reliability of Cloud Platform itself: on-call, incident response, postmortems, runbooks, and prevention.
- Use AI tooling daily to accelerate development, testing, IaC, operations, and investigations, and help the team raise its AI leverage.
What we're looking for
- 6+ years building and operating large-scale distributed systems with a focus on infrastructure and cloud, especially compute foundations.
- Deep, hands-on experience operating and troubleshooting Kubernetes in production, including control-plane, node, and networking issues, ideally Amazon EKS at fleet scale.
- Strong AWS experience: EKS, EC2, Lambda, API Gateway, VPC networking, IAM, S3, KMS. Bedrock is a plus.
- Multi-account AWS (20+ accounts) experience, including Transit Gateway, PrivateLink, VPC routing, DNS, and load balancing.
- Infrastructure-as-code at scale with Terraform (CDK experience is a plus).
- Fluent coding in at least one language (Go, Python, or TypeScript/Node.js preferred).
- Experience with hybrid monolith/microservices architectures.
- Experience operating data stores at scale, such as PostgreSQL, DynamoDB, S3, and Redis/Valkey.
- Track record of improving infrastructure reliability and efficiency and implementing security guardrails.
- Strong production debugging across application and infrastructure boundaries, clear written communication, and effective cross-functional collaboration.
- Daily AI user with concrete examples of how AI supercharged your engineering workflow.
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: Seoul, South Korea
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 Regional Research Economist at Anthropic, you will collaborate with governments, academia, industry, and civil society in your region to measure and understand AI’s effects on the economy and explore research-driven policy interventions. You will contribute to the development of the Anthropic Economic Index and its extension to generate regionally relevant insights, establish new methodologies to measure the usage, diffusion, and impact of AI throughout the economy, and work to broaden access to and usage of the insights generated by the Index. You will use frontier methods in econometrics, machine learning, and structural estimation. Such rigor will drive impact, shaping both policy discussions externally and informing Anthropic’s internal business and product decisions.
Our team combines rigorous empirical methods with novel measurement approaches. We’re building first-of-its-kind datasets tracking AI’s impact on labor markets, productivity, and economic transformation. Using our privacy-preserving measurement system (
Clio
), we
analyze millions of real-world AI interactions
to understand how AI augments and automates work across different occupations and tasks.
For this role, we’re looking for candidates who can combine rigorous economic analysis with novel measurement approaches to understand AI’s transformative effects on the economy. The ideal candidate will be comfortable working at the intersection of empirical economics, technological change, and policy impact.
Key responsibilities
Build and maintain relationships with academic institutions, policy think tanks, and other research partners as the primary point of contact for these organizations on economic impact work in your region
Advance research collaborations that answer country- or regional-specific economic impact questions
Translate research insights into actionable recommendations for policy discussions
Make fundamental contributions to the development and expansion of the
Anthropic Economic Index
, including country- and regional-specific analysis
Design and collaborate on empirical research on AI’s economic effects with governments, academia, industry, and civil society in your region
Develop new methodological approaches, in collaboration with partners in your region, for studying AI’s impact on labor markets and the future of work; productivity and task transformation; economic inequality and displacement; industry-specific disruption and adaptation; and aggregate economic trajectories (GDP, productivity, unemployment) under varying AI-adoption scenarios
Work cross-functionally with other technical teams to improve our measurement infrastructure and data collection
Amplify external engagement through research publications, policy briefs, and presentations to diverse stakeholders
Minimum qualifications
PhD in Economics
Strong track record of empirical research, particularly studies combining novel data sources and economic theory or implementing frontier methods in causal inference and machine learning
Demonstrated experience working in, and relevant relationships across, the region
Proficiency in Python, R, SQL, or similar tools for large-scale data analysis
Demonstrated ability to lead complex research projects from conception to publication
Demonstrated ability to communicate technical findings to diverse audiences
Demonstrated ability to build relationships across academic, policy, and industry communities
Preferred qualifications
Experience relevant to the study of AI’s impact on the economy, such as labor market analysis and occupational change; task-based approaches to technological transformation; large-scale data analysis and econometric methods; large language models for social science research; policy-relevant economic research; experimental and quasi-experimental methods for causal inference; macroeconomic modeling and time series forecasting; or agent-based modeling and large-scale simulation
Experience working with novel datasets and measurement systems
Comfort learning new technical tools and frameworks
Strong interest in ensuring AI development benefits humanity
Comfort working with AI systems and ability to think critically about their capabilities and limitations
Representative projects
How Australia Uses Claude: Findings from the Anthropic Economic Index
Anthropic Economic Index Report: Economic Primitives
Anthropic Economic Index Report: Uneven Geographic and Enterprise AI Adoption
Estimating AI productivity gains from Claude conversations
The Anthropic Economic Index
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: Sydney, Australia
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 Regional Research Economist at Anthropic, you will collaborate with governments, academia, industry, and civil society in your region to measure and understand AI’s effects on the economy and explore research-driven policy interventions. You will contribute to the development of the Anthropic Economic Index and its extension to generate regionally relevant insights, establish new methodologies to measure the usage, diffusion, and impact of AI throughout the economy, and work to broaden access to and usage of the insights generated by the Index. You will use frontier methods in econometrics, machine learning, and structural estimation. Such rigor will drive impact, shaping both policy discussions externally and informing Anthropic’s internal business and product decisions.
Our team combines rigorous empirical methods with novel measurement approaches. We’re building first-of-its-kind datasets tracking AI’s impact on labor markets, productivity, and economic transformation. Using our privacy-preserving measurement system (
Clio
), we
analyze millions of real-world AI interactions
to understand how AI augments and automates work across different occupations and tasks.
For this role, we’re looking for candidates who can combine rigorous economic analysis with novel measurement approaches to understand AI’s transformative effects on the economy. The ideal candidate will be comfortable working at the intersection of empirical economics, technological change, and policy impact.
Key responsibilities
Build and maintain relationships with academic institutions, policy think tanks, and other research partners as the primary point of contact for these organizations on economic impact work in your region
Advance research collaborations that answer country- or regional-specific economic impact questions
Translate research insights into actionable recommendations for policy discussions
Make fundamental contributions to the development and expansion of the
Anthropic Economic Index
, including country- and regional-specific analysis
Design and collaborate on empirical research on AI’s economic effects with governments, academia, industry, and civil society in your region
Develop new methodological approaches, in collaboration with partners in your region, for studying AI’s impact on labor markets and the future of work; productivity and task transformation; economic inequality and displacement; industry-specific disruption and adaptation; and aggregate economic trajectories (GDP, productivity, unemployment) under varying AI-adoption scenarios
Work cross-functionally with other technical teams to improve our measurement infrastructure and data collection
Amplify external engagement through research publications, policy briefs, and presentations to diverse stakeholders
Minimum qualifications
PhD in Economics
Strong track record of empirical research, particularly studies combining novel data sources and economic theory or implementing frontier methods in causal inference and machine learning
Demonstrated experience working in, and relevant relationships across, the region
Proficiency in Python, R, SQL, or similar tools for large-scale data analysis
Demonstrated ability to lead complex research projects from conception to publication
Demonstrated ability to communicate technical findings to diverse audiences
Demonstrated ability to build relationships across academic, policy, and industry communities
Preferred qualifications
Experience relevant to the study of AI’s impact on the economy, such as labor market analysis and occupational change; task-based approaches to technological transformation; large-scale data analysis and econometric methods; large language models for social science research; policy-relevant economic research; experimental and quasi-experimental methods for causal inference; macroeconomic modeling and time series forecasting; or agent-based modeling and large-scale simulation
Experience working with novel datasets and measurement systems
Comfort learning new technical tools and frameworks
Strong interest in ensuring AI development benefits humanity
Comfort working with AI systems and ability to think critically about their capabilities and limitations
Representative projects
How Australia Uses Claude: Findings from the Anthropic Economic Index
Anthropic Economic Index Report: Economic Primitives
Anthropic Economic Index Report: Uneven Geographic and Enterprise AI Adoption
Estimating AI productivity gains from Claude conversations
The Anthropic Economic Index
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.
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