Location: Republic of Ireland (Remote)
Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at
grafana.com
and follow us on
LinkedIn
and
X
.
We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do.
You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity.
This is a remote opportunity, and we would be interested in applicants located in Spain, Sweden, UK, Ireland or Germany.
The Opportunity:
At Grafana Labs, we build observability tools that help users understand, respond to, and improve their systems – regardless of scale, complexity, or tech stack. We recently started a skunkworks initiative with a mission to bring observability to the rest of the business. Our goal is to make Grafana the single best place where humans and AI agents understand and act on real-time data from across the enterprise. As part of this initiative, we are building an AI-native data intelligence system that gives agents reliable, governed access to enterprise context. This system helps agents retrieve the right data, metadata, definitions, lineage, quality signals, and institutional knowledge without every agent builder having to maintain their own brittle context files. The principle is simple: the context system retrieves, agents decide, and data teams maintain the intelligence.
The new team is a mix of seasoned Grafanistas and new hires. We operate with a high degree of autonomy and ownership, both as individuals and as a team. Engineers are empowered to make decisions, move quickly, and validate ideas early – while being supported by a deeply collaborative culture that values curiosity, feedback, and cross-functional partnership.
We’re looking for a Staff-level Backend Engineer to help build the first production services for this context layer management system. You will design and ship the core backend architecture that powers ingestion, context storage, retrieval APIs, and agent-facing integrations. This is an early-stage role on a high-autonomy team, so you should be comfortable working through ambiguity, making pragmatic architectural decisions, and building systems that can evolve from internal dogfooding to production-grade SaaS. As the team matures, there’s a broad opportunity to expand or redefine this role based on impact and initiative.
What You'll Be Doing:
Build the core backend services: Design, implement, test, and operate the first services for context ingestion, context indexing, retrieval orchestration, API access, source configuration, and system administration.
Create a scalable SaaS foundation: Help define and build the architecture for a multi-tenant service, including tenant isolation, usage tracking, quotas, audit logs, background jobs, and reliable service boundaries.
Power agent-facing retrieval workflows: Build APIs and service interfaces that allow AI agents, MCP tools, CLIs, and internal applications to retrieve relevant context, provenance, confidence signals, and warnings.
Work across product and infrastructure: Partner with the team to make practical tradeoffs between fast experimentation and long-term reliability, especially as the project moves from prototype to production.
Operate what you build: Instrument services with metrics, logs, traces, alerts, and dashboards. Use observability tools to understand system behavior and improve reliability.
Contribute to technical direction: Help shape the architecture, service boundaries, storage choices, API contracts, deployment patterns, and engineering practices for a new product area.
Effective communication: You’ll be working in a highly dynamic and collaborative environment, so we need someone who can communicate effectively and contribute across teams.
Ownership and impact: Take full ownership of the AI solutions you develop, ensuring they are not only innovative but also scalable, maintainable, and aligned with real user workflows.
What Makes You a Great Fit:
Strong engineering skills: Solid experience building production-grade, user-facing software systems. You’re a self-starter, capable of tackling complex engineering problems and making UI design decisions with minimal supervision.
AI experience with a practical mindset: You’re familiar with AI technologies and frameworks, and you focus on delivering high-quality solutions that work in the real world, not just in theory.
Quick iteration and experimentation: You’re comfortable releasing prototypes, collecting feedback, and iterating with a pragmatic mindset.
Proven initiative: You take ownership and drive projects forward, pushing boundaries to find the most impactful solutions. You can deal with ambiguity and are able to define scope where things are loosely defined.
Collaborative attitude: You communicate effectively with your peers. You’re open to feedback, and you bring a solutions-oriented mindset to the table.
Experience with LLMs, prompt engineering, and building applications powered by GenAI.
Proven track record of delivering software that made it into production and is actively used by users.
Exposure to working in cloud-native environments (e.g., AWS, GCP, Azure).
Experience using observability tools to understand and troubleshoot system behavior.
Bonus Points for:
Experience building or working with agent frameworks or multi‑agent workflows.
Experience as a data analyst or work with data platforms (e.g., Looker, Tableau, PowerBI, Snowflake, DataBricks)
Experience building tools for data engineering.
How we work:
We are a remote-first team that meets regularly over video and does most of our work asynchronously, in writing. We value creativity, diverse perspectives, and clear communication. Tempo is relied upon by prominent global organizations to monitor critical applications and infrastructure, and we expect everyone on the team, including our Staff engineers, to contribute ideas that make it a more reliable, more useful, and more loved product.
Compensation & Rewards:
In the Republic of Ireland, the Base compensation range for this role is EUR
107,000
- EUR
134,000
. Actual compensation may vary based on level, experience, and skillset as assessed in the interview process. Benefits include equity, bonus (if applicable) and other benefits listed
here
.
*Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process
*Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process.
Why You’ll Thrive at Grafana Labs:
100% Remote, Global Culture -
As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose.
Scaling Organization
– Tackle meaningful work in a high-growth, ever-evolving environment.
Transparent Communication
– Expect open decision-making and regular company-wide updates.
Innovation-Driven
– Autonomy and support to ship great work and try new things.
Open Source Roots
– Built on community-driven values that shape how we work.
Empowered Teams
– High trust, low ego culture that values outcomes over optics.
Career Growth Pathways
– Defined opportunities to grow and develop your career.
Approachable Leadership
– Transparent execs who are involved, visible, and human.
Passionate People
– Join a team of smart, supportive folks who care deeply about what they do.
In-Person onboarding
- We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it.
Balance is Key
- We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect.
*We will comply with local legislation where applicable.
Equal Opportunity Employer:
Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law. We believe that equality and diversity build a strong organisation, and we work hard to ensure that is the foundation of our organisation as we grow.
Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings.
#LI-Remote
For information about how your personal data is used once you’ve applied to a job, check out our
privacy policy
.
seniorRepublic of Ireland (Remote); Ownership and impact: Take full ownership of the AI solutions you develop, ensuring they are not only innovative but also scalable, maintainable, and aligned with real user workflows
Location: Sweden (Remote)
Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at
grafana.com
and follow us on
LinkedIn
and
X
.
We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do.
You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity.
This is a remote opportunity, and we would be interested in applicants located in Spain, Sweden, UK, Ireland or Germany.
The Opportunity:
At Grafana Labs, we build observability tools that help users understand, respond to, and improve their systems – regardless of scale, complexity, or tech stack. We recently started a skunkworks initiative with a mission to bring observability to the rest of the business. Our goal is to make Grafana the single best place where humans and AI agents understand and act on real-time data from across the enterprise. As part of this initiative, we are building an AI-native data intelligence system that gives agents reliable, governed access to enterprise context. This system helps agents retrieve the right data, metadata, definitions, lineage, quality signals, and institutional knowledge without every agent builder having to maintain their own brittle context files. The principle is simple: the context system retrieves, agents decide, and data teams maintain the intelligence.
The new team is a mix of seasoned Grafanistas and new hires. We operate with a high degree of autonomy and ownership, both as individuals and as a team. Engineers are empowered to make decisions, move quickly, and validate ideas early – while being supported by a deeply collaborative culture that values curiosity, feedback, and cross-functional partnership.
We’re looking for a Staff-level Backend Engineer to help build the first production services for this context layer management system. You will design and ship the core backend architecture that powers ingestion, context storage, retrieval APIs, and agent-facing integrations. This is an early-stage role on a high-autonomy team, so you should be comfortable working through ambiguity, making pragmatic architectural decisions, and building systems that can evolve from internal dogfooding to production-grade SaaS. As the team matures, there’s a broad opportunity to expand or redefine this role based on impact and initiative.
What You'll Be Doing:
Build the core backend services: Design, implement, test, and operate the first services for context ingestion, context indexing, retrieval orchestration, API access, source configuration, and system administration.
Create a scalable SaaS foundation: Help define and build the architecture for a multi-tenant service, including tenant isolation, usage tracking, quotas, audit logs, background jobs, and reliable service boundaries.
Power agent-facing retrieval workflows: Build APIs and service interfaces that allow AI agents, MCP tools, CLIs, and internal applications to retrieve relevant context, provenance, confidence signals, and warnings.
Work across product and infrastructure: Partner with the team to make practical tradeoffs between fast experimentation and long-term reliability, especially as the project moves from prototype to production.
Operate what you build: Instrument services with metrics, logs, traces, alerts, and dashboards. Use observability tools to understand system behavior and improve reliability.
Contribute to technical direction: Help shape the architecture, service boundaries, storage choices, API contracts, deployment patterns, and engineering practices for a new product area.
Effective communication: You’ll be working in a highly dynamic and collaborative environment, so we need someone who can communicate effectively and contribute across teams.
Ownership and impact: Take full ownership of the AI solutions you develop, ensuring they are not only innovative but also scalable, maintainable, and aligned with real user workflows.
What Makes You a Great Fit:
Strong engineering skills: Solid experience building production-grade, user-facing software systems. You’re a self-starter, capable of tackling complex engineering problems and making UI design decisions with minimal supervision.
AI experience with a practical mindset: You’re familiar with AI technologies and frameworks, and you focus on delivering high-quality solutions that work in the real world, not just in theory.
Quick iteration and experimentation: You’re comfortable releasing prototypes, collecting feedback, and iterating with a pragmatic mindset.
Proven initiative: You take ownership and drive projects forward, pushing boundaries to find the most impactful solutions. You can deal with ambiguity and are able to define scope where things are loosely defined.
Collaborative attitude: You communicate effectively with your peers. You’re open to feedback, and you bring a solutions-oriented mindset to the table.
Experience with LLMs, prompt engineering, and building applications powered by GenAI.
Proven track record of delivering software that made it into production and is actively used by users.
Exposure to working in cloud-native environments (e.g., AWS, GCP, Azure).
Experience using observability tools to understand and troubleshoot system behavior.
Bonus Points for:
Experience building or working with agent frameworks or multi‑agent workflows.
Experience as a data analyst or work with data platforms (e.g., Looker, Tableau, PowerBI, Snowflake, DataBricks)
Experience building tools for data engineering.
How we work:
We are a remote-first team that meets regularly over video and does most of our work asynchronously, in writing. We value creativity, diverse perspectives, and clear communication. Tempo is relied upon by prominent global organizations to monitor critical applications and infrastructure, and we expect everyone on the team, including our Staff engineers, to contribute ideas that make it a more reliable, more useful, and more loved product.
Compensation & Rewards:
In Sweden, the Base compensation range for this role is SEK
878,578
- SEK
1,054,294
. Actual compensation may vary based on level, experience, and skillset as assessed in the interview process. Benefits include equity, bonus (if applicable) and other benefits listed
here
.
*Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process
*Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process.
Why You’ll Thrive at Grafana Labs:
100% Remote, Global Culture -
As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose.
Scaling Organization
– Tackle meaningful work in a high-growth, ever-evolving environment.
Transparent Communication
– Expect open decision-making and regular company-wide updates.
Innovation-Driven
– Autonomy and support to ship great work and try new things.
Open Source Roots
– Built on community-driven values that shape how we work.
Empowered Teams
– High trust, low ego culture that values outcomes over optics.
Career Growth Pathways
– Defined opportunities to grow and develop your career.
Approachable Leadership
– Transparent execs who are involved, visible, and human.
Passionate People
– Join a team of smart, supportive folks who care deeply about what they do.
In-Person onboarding
- We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it.
Balance is Key
- We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect.
*We will comply with local legislation where applicable.
Equal Opportunity Employer:
Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law. We believe that equality and diversity build a strong organisation, and we work hard to ensure that is the foundation of our organisation as we grow.
Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings.
#LI-Remote
For information about how your personal data is used once you’ve applied to a job, check out our
privacy policy
.
Location: Spain (Remote)
Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at
grafana.com
and follow us on
LinkedIn
and
X
.
We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do.
You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity.
This is a remote opportunity, and we would be interested in applicants located in Spain, Sweden, UK, Ireland or Germany.
The Opportunity:
At Grafana Labs, we build observability tools that help users understand, respond to, and improve their systems – regardless of scale, complexity, or tech stack. We recently started a skunkworks initiative with a mission to bring observability to the rest of the business. Our goal is to make Grafana the single best place where humans and AI agents understand and act on real-time data from across the enterprise. As part of this initiative, we are building an AI-native data intelligence system that gives agents reliable, governed access to enterprise context. This system helps agents retrieve the right data, metadata, definitions, lineage, quality signals, and institutional knowledge without every agent builder having to maintain their own brittle context files. The principle is simple: the context system retrieves, agents decide, and data teams maintain the intelligence.
The new team is a mix of seasoned Grafanistas and new hires. We operate with a high degree of autonomy and ownership, both as individuals and as a team. Engineers are empowered to make decisions, move quickly, and validate ideas early – while being supported by a deeply collaborative culture that values curiosity, feedback, and cross-functional partnership.
We’re looking for a Staff-level Backend Engineer to help build the first production services for this context layer management system. You will design and ship the core backend architecture that powers ingestion, context storage, retrieval APIs, and agent-facing integrations. This is an early-stage role on a high-autonomy team, so you should be comfortable working through ambiguity, making pragmatic architectural decisions, and building systems that can evolve from internal dogfooding to production-grade SaaS. As the team matures, there’s a broad opportunity to expand or redefine this role based on impact and initiative.
What You'll Be Doing:
Build the core backend services: Design, implement, test, and operate the first services for context ingestion, context indexing, retrieval orchestration, API access, source configuration, and system administration.
Create a scalable SaaS foundation: Help define and build the architecture for a multi-tenant service, including tenant isolation, usage tracking, quotas, audit logs, background jobs, and reliable service boundaries.
Power agent-facing retrieval workflows: Build APIs and service interfaces that allow AI agents, MCP tools, CLIs, and internal applications to retrieve relevant context, provenance, confidence signals, and warnings.
Work across product and infrastructure: Partner with the team to make practical tradeoffs between fast experimentation and long-term reliability, especially as the project moves from prototype to production.
Operate what you build: Instrument services with metrics, logs, traces, alerts, and dashboards. Use observability tools to understand system behavior and improve reliability.
Contribute to technical direction: Help shape the architecture, service boundaries, storage choices, API contracts, deployment patterns, and engineering practices for a new product area.
Effective communication: You’ll be working in a highly dynamic and collaborative environment, so we need someone who can communicate effectively and contribute across teams.
Ownership and impact: Take full ownership of the AI solutions you develop, ensuring they are not only innovative but also scalable, maintainable, and aligned with real user workflows.
What Makes You a Great Fit:
Strong engineering skills: Solid experience building production-grade, user-facing software systems. You’re a self-starter, capable of tackling complex engineering problems and making UI design decisions with minimal supervision.
AI experience with a practical mindset: You’re familiar with AI technologies and frameworks, and you focus on delivering high-quality solutions that work in the real world, not just in theory.
Quick iteration and experimentation: You’re comfortable releasing prototypes, collecting feedback, and iterating with a pragmatic mindset.
Proven initiative: You take ownership and drive projects forward, pushing boundaries to find the most impactful solutions. You can deal with ambiguity and are able to define scope where things are loosely defined.
Collaborative attitude: You communicate effectively with your peers. You’re open to feedback, and you bring a solutions-oriented mindset to the table.
Experience with LLMs, prompt engineering, and building applications powered by GenAI.
Proven track record of delivering software that made it into production and is actively used by users.
Exposure to working in cloud-native environments (e.g., AWS, GCP, Azure).
Experience using observability tools to understand and troubleshoot system behavior.
Bonus Points for:
Experience building or working with agent frameworks or multi‑agent workflows.
Experience as a data analyst or work with data platforms (e.g., Looker, Tableau, PowerBI, Snowflake, DataBricks)
Experience building tools for data engineering.
How we work:
We are a remote-first team that meets regularly over video and does most of our work asynchronously, in writing. We value creativity, diverse perspectives, and clear communication. Tempo is relied upon by prominent global organizations to monitor critical applications and infrastructure, and we expect everyone on the team, including our Staff engineers, to contribute ideas that make it a more reliable, more useful, and more loved product.
Compensation & Rewards:
In Spain, the Base compensation range for this role is EUR
94,025
- EUR
112,830
. Actual compensation may vary based on level, experience, and skillset as assessed throughout the interview process. All of our roles include Restricted Stock Units (RSUs), giving every team member ownership in Grafana Labs' success. We believe in shared outcomes—RSUs help us stay aligned and invested as we scale globally.
*Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process.
Why You’ll Thrive at Grafana Labs:
100% Remote, Global Culture -
As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose.
Scaling Organization
– Tackle meaningful work in a high-growth, ever-evolving environment.
Transparent Communication
– Expect open decision-making and regular company-wide updates.
Innovation-Driven
– Autonomy and support to ship great work and try new things.
Open Source Roots
– Built on community-driven values that shape how we work.
Empowered Teams
– High trust, low ego culture that values outcomes over optics.
Career Growth Pathways
– Defined opportunities to grow and develop your career.
Approachable Leadership
– Transparent execs who are involved, visible, and human.
Passionate People
– Join a team of smart, supportive folks who care deeply about what they do.
In-Person onboarding
- We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it.
Balance is Key
- We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect.
*We will comply with local legislation where applicable.
Equal Opportunity Employer:
Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law. We believe that equality and diversity build a strong organisation, and we work hard to ensure that is the foundation of our organisation as we grow.
Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings.
#LI-Remote
For information about how your personal data is used once you’ve applied to a job, check out our
privacy policy
.
Location: San Francisco, CA | Seattle, WA | 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
Anthropic's Supplier Security & Assurance (SSA) team sits within Security GRC and is responsible for assessing the security of our suppliers: evaluating whether vendors meet our security requirements, capturing the deviations, and giving the business a clear approval decision it can act on. We assess the vendor population a frontier AI lab actually depends on: SaaS and software, human data operations, compute and data center providers, hardware suppliers, and services firms. The program is designed agent-first so that people spend their time on judgment, remediation, and the vendors that matter most.
As a member of the Supplier Security & Assurance team you will run supplier security assessments end to end: reviewing evidence, verifying agent-drafted evaluations, determining inherent and residual risk, and driving findings to closure with vendors and business owners. You will also carry the work that extends assurance past the approval, from contractual security terms and secure configuration baselines to continuous monitoring and reassessment, and you will help shape the tooling and requirements the program runs on.
Key responsibilities
Run supplier security assessments: review agent-prefilled outputs, evaluate vendor controls and evidence, determine residual risk, route to domain reviewers where deeper assessment is warranted
Operate supplier issue management and risk treatment: document each finding with a severity, an owner, and a due date, drive remediation with the vendor and the business owner, record risk acceptances, and roll open issues up to the risk register
Run continuous monitoring after approval: reopen an assessment on defined triggers (data classification change, new SOC 2 report, new subprocessor, vendor incident), investigate SaaS configuration, data, and use case drift signals, and queue a reassessment where the vendor's scope has moved
Improve the program as you run it: identify gaps in coverage, questionnaires, requirements, and tooling that surface during assessments, propose the fix, and carry roadmap items that mature supplier security overall
Tune and maintain our Claude-powered assessment platform alongside the team: prompt development, questionnaire and assessment type design, calibration against assessor decisions, and output QA
Contribute to KPI and KRI reporting on coverage, cycle time, residual risk, open issues, and reassessments due
Minimum qualifications
Experience running supplier security assessments end to end at a technology company: scoping the engagement, determining inherent risk, reviewing controls and evidence, documenting residual risk, and driving findings to closure
Working knowledge of risk fundamentals (inherent and residual risk, control effectiveness, compensating controls, risk acceptance) and the judgment to apply them when the evidence is incomplete or the answer isn't in a framework
Ability to assess a vendor across security domains, and to recognize which findings you can close yourself and which need a security domain specialist
Track record of driving risk treatment to closure through influence across teams with competing priorities
Experience building or tuning an LLM-backed workflow, agent, or automation in a risk, compliance, or operations context, including tuning prompts and reviewing model output for accuracy
Experience building or operating issue management workflows: logging issues with a clear owner and due date, tracking remediation, and escalating when treatment stalls
Working technical knowledge of SaaS security configuration (SSO and SCIM, admin scoping, sharing defaults, audit log export) and of standard vendor security contract terms (DPA, incident notification, subprocessors, audit and testing rights)
Ability to read a SOC 2 report or penetration test and turn it into findings: identify control exceptions and carve-outs, map complementary user entity controls, and judge what the evidence does and does not prove
Preferred qualifications
Experience assessing cloud infrastructure, data center, or data-pipeline vendors
Experience supporting SOX, SOC 2, or ISO 27001 third party or vendor management controls
Experience assessing additional, more specialized vendor cohorts from a security risk perspective: human data operations or data labeling vendors, hardware suppliers, compute providers and neoclouds, and others
Experience with post-approval supplier continuous monitoring: configuration, data, and use case drift detection, shadow IT & SaaS detection, vendor incident management, or evidence-based vendor audits/site visits
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:
$255,000
—
$270,000 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.
For roles performing work in California:
We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.
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: Philippines
Workplace: Remote
ABOUT THE ROLE
The Compute & Infrastructure Accounting team supports accounting and financial reporting for OpenAI’s rapidly evolving cloud computing, data center, server, equipment, colocation, software and data, and other AI infrastructure arrangements. We’re seeking a hands-on Contract Accountant to support recurring close and day-to-day operational accounting for these costs.
The contractor will translate contract terms, pricing, delivery, usage, invoices, and operational data into accurate accruals, true-ups, journal-entry support, reconciliations, and variance explanations. This role works closely with Compute & Infrastructure Accounting, Technical Accounting, Procurement, Strategic Finance, Data Engineering, and external vendors to resolve exceptions and keep accounting outputs timely, complete, and audit-ready. The contractor will use approved AI tools to reduce manual effort, strengthen analysis, improve documentation, and create scalable operating leverage.
This role does not make final accounting conclusions or approve journals, payments, vendors, contracts, or access; it does not negotiate contracts or commit company funds. Success is measured by accurate and timely close deliverables, well-supported reconciliations, prompt exception resolution, dependable cross-functional communication, and adherence to established controls.
RESPONSIBILITIES
LEASE AND FIXED ASSET ACCOUNTING
- Own assigned month-end and quarter-end lease-accounting activities, including journal entries, rollforwards, account reconciliations, balance-sheet substantiation, and flux or variance analysis.
- Prepare complete, accurate, and reviewer-ready journal entries and supporting schedules for lease-related balances, including right-of-use assets, lease liabilities, rent expense, interest, amortization, remeasurements, and true-ups.
- Perform reconciliations over lease accounts and subledger-to-general-ledger balances; investigate reconciling items, document conclusions, and drive timely resolution.
- Perform fixed-asset accounting as assigned, including additions, transfers, placed-in-service assessments, depreciation, disposals, construction-in-progress activity, reconciliations, and period-end entries.
CONTRACT REVIEW AND LEASE-SYSTEM ADMINISTRATION
- Read and analyze large, complex lease contracts, amendments, renewals, extensions, and termination agreements to identify relevant accounting terms, payment streams, options, incentives, obligations, and effective dates.
- Accurately enter new leases, modifications, remeasurements, and terminations into the lease-accounting system based on a complete understanding of the underlying contract.
- Validate lease-system inputs and outputs against executed agreements, payment schedules, invoices, commencement evidence, and operational data; resolve completeness and accuracy exceptions.
- Compile and validate information supporting quarterly and annual lease footnote disclosures, including maturity analyses, expense classifications, weighted-average metrics, cash-flow information, and required tie-outs.
CONTROLS, AUDIT, AND ISSUE RESOLUTION
- Follow U.S. GAAP, established lease-accounting and fixed-asset policies, standard operating procedures, close calendars, review requirements, and approval workflows.
- Execute control procedures over lease populations, contract abstraction, system inputs, calculations, reconciliations, disclosures, and workpapers, including completeness and accuracy checks and evidence retention.
- Respond to internal and external audit requests by assembling contracts, tie-outs, schedules, explanations, control evidence, and other supporting documentation.
- Investigate accounting and control exceptions, document root causes and resolutions, track open items through completion, and escalate significant matters promptly.
CROSS-FUNCTIONAL COORDINATION
- Partner with Compute & Infrastructure Accounting, Technical Accounting, Finance Systems, Data, Engineering, and business teams to resolve contract, data, system, accounting, and operational issues.
- Coordinate with Legal, Procurement, FP&A, Accounts Payable, Treasury, and other stakeholders to obtain executed agreements, validate facts, and support complete and timely lease accounting.
- Communicate requirements, status, outstanding items, and accounting implications clearly to finance and non-finance stakeholders, and escalate judgmental matters with clear context and recommended next steps.
PROCESS DISCIPLINE AND CONTINUOUS IMPROVEMENT
- Identify recurring contract, data-quality, system, process, and control issues; surface trends and recommend scalable improvements.
- Write clear business requirements, test lease-system or process changes, and validate downstream accounting outputs before operational use.
- Improve recurring lease and fixed-asset workflows through standardization, documentation, automation, and tooling; maintain clear procedures and handoffs.
- Use approved AI-enabled tools responsibly to support contract review, data validation, analysis, and documentation while following data-security and review requirements.
- Help maintain consistent, controlled execution as the infrastructure portfolio, accounting requirements, systems, and workflows evolve.
REQUIRED SKILLS AND EXPERIENCE
- Progressive experience in accounting, audit, advisory, or a related finance function, including hands-on operational accounting and ownership of recurring close deliverables.
- Strong month-end and quarter-end close experience involving journal entries, account reconciliations, rollforwards, variance analysis, and reviewer-ready workpaper preparation.
- Strong working knowledge of U.S. GAAP and internal controls, with the judgment to identify and escalate matters requiring technical accounting review.
- Demonstrated ability to read and interpret lengthy, complex contracts and translate legal and commercial terms into accurate accounting conclusions, system inputs, and supporting documentation.
- Advanced spreadsheet and data-analysis skills, including the ability to work accurately with large datasets, and experience using an ERP or comparable finance system.
- Experience operating with high attention to detail in a fast-paced, deadline-driven environment while managing multiple agreements, systems, and stakeholders.
- Strong analytical, problem-solving, and organizational skills; sound judgment; and clear documentation habits.
- Excellent written and verbal communication skills and the ability to partner effectively across accounting, finance, legal, systems, data, engineering, and business teams.
PREFERRED
- Hands-on lease-accounting experience under ASC 842, including contract abstraction, classification, measurement, modifications, reconciliations, and disclosure support.
- Hands-on fixed-asset accounting experience, including additions, depreciation, disposals, transfers, construction in progress, and related reconciliations.
- Experience with lease-accounting software and an ERP such as Oracle Fusion; CPA, CA, or an equivalent professional accounting qualification is a plus.
- Experience preparing or reviewing cash flow statements, including cash flow classification and presentation for lease and fixed-asset activity.
NICE-TO-HAVE
- Experience in a technology, cloud-computing, data-center, colocation, equipment, or other infrastructure-intensive environment.
- Familiarity with SQL, data-query tools, issue-tracking tools, or similar technical tools used to investigate data, system, and process issues.
- Experience supporting SEC reporting, lease footnote disclosures, or public-company audit requirements in a high-growth or control-focused environment.
- Experience with process automation, systems implementation, or workflow redesign, and collaborating across time zones with distributed teams and external service providers.
Location: United States
At Reltio®, an SAP Company, we believe data should fuel your success in the enterprise AI era. Our Context Intelligence Platform turns fragmented data into a trusted, connected context so AI agents and systems can act with expert-level judgement at enterprise scale. Reltio’s cloud-native SaaS platform harmonizes, unifies, and governs data across sources and formats—including unstructured data—in real time, turning them into data assets that can be mobilized in milliseconds to any application, user, or AI agent. Trusted by more than 200 of the world’s largest brands across industries such as life sciences, financial services, healthcare, and technology, we fuel frictionless operations and help enterprises accelerate innovation and reduce risk.
At Reltio, our values guide everything we do. With an unyielding commitment to prioritizing our “Customer First”, we strive to ensure their success. We embrace our differences and are “Better Together” as One Reltio. We are always looking to “Simplify and Share” our knowledge when we collaborate to remove obstacles for each other. We hold ourselves accountable for our actions and outcomes and strive for excellence. We “Own It”. Every day, we innovate and evolve, so that today is “Always Better Than Yesterday”. If you share and embody these values, we invite you to join our team at Reltio and contribute to our mission of excellence.
Reltio has earned numerous awards and industry and analyst recognition for our technology, our culture, and our people. Reltio was founded on a distributed workforce and offers flexible work arrangements to help our people manage their personal and professional lives. If you’re ready to work on unrivaled technology where your desire to be part of a collaborative team is met with a laser-focused mission to enable digital transformation with connected data, let’s talk!
Job Summary:
In this strategic role as a
Solution Architect
in Professional Services, you are an individual contributor, showcasing expertise in MDM design patterns and program-level strategies, adhering to MDM principles and best practices. Your focus will be on ensuring the quality, efficiency, and accuracy of implementations for Reltio, our partners, and customers. This pivotal role encompasses oversight of customer-facing, partner-facing, and internal processes, positioning you as the foremost technical authority within Professional Services.
Job Duties and Responsibilities:
Being a senior technical resource on the team with deep and demonstrable knowledge of technology, architectural design, integration patterns, MDM as well as good understanding of Reltio’s capabilities and direction
Oversees technical and architectural Reltio MDM solution designs, ensuring alignment with the company’s standards and client requirements
Design robust agentic workflows using Reltio’s Agent Flow platform that integrate with core systems and event sources.
Contribute to internal Agentic tooling, playbooks, and best-practice documentation and framework.
Manages and takes responsibility for Reltio deliverables maintaining a proven track record in delivering successful Professional Services engagements.
Applies Reltio's best practices in a prescriptive manner
Leads & guides Reltio Customer and Partner technical team
Responsible for the definition & design the Reltio MDM solution and architecture for Customer implementations leveraging MDM principles and Reltio's best practices
Ensures quality, efficiency and accuracy of implementations for Reltio, our implementations partner and our customers
Support multiple customer projects simultaneously with onshore & offshore team members
Coordinates with Product Management, Engineering, Development Operations, Customer Success if needed
Develops meaningful and trusted relations with customer and partner resources
Develops repeatable assets such as methodologies, tools, templates, guidelines for the betterment of the Professional Services practice
Excellent communication skills - written and verbal
Skills You Must Have:
At least 6 years of overall technology implementations and progressive delivery in a technology or professional services organization delivering moderate to complex technology solutions
Ideally have 2 years experience with MDM platforms and has completed 2 MDM implementations
Experience deploying and operationalizing LLM- or agentic systems (prompting, orchestration, evaluation, guardrails).
Knowledge of Software as a Service (SaaS), Cloud delivery, and other SaaS platforms/solutions
Knowledge of CRM (Salesforce, Veeva), ERP, accounting systems and provisioning systems is recommended
Experience with Object Oriented technologies
Experience with business process and governance is recommended
Industry / Domain experience
Minimum Bachelor's degree in Computer Science, Engineering, or a technical field
Master's degree in a technical field is recommended
Certifications in Java, Scrum/Agile methodology, cloud provider certifications
At Reltio, we carefully consider a wide range of compensation factors to determine your personal top of market. We rely on market indicators to determine compensation and your specific job family, background, skills, and experience to get it right. These considerations can cause your compensation to vary and will also be dependent on your location.
Overall Market Range
$114,000
—
$240,000 USD
Reltio is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Reltio is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities.
Location: Canada Wide - Excluding Quebec; British Columbia
Workplace: Hybrid
ABOUT THE ROLE
Safe Software is looking for a Staff AI Engineer to design, build, and deploy production-grade AI systems across the organization.
This is a hands-on engineering role responsible for the full AI lifecycle, from data preparation and model development through evaluation, deployment, monitoring, and continuous improvement. You will work across generative AI, applied machine learning, retrieval, and agentic systems while establishing reusable architectures and engineering standards for complex production implementations.
ABOUT THE TEAM
AI Enablement helps Safe Software adopt AI effectively and responsibly. The team builds shared capabilities, platforms, and engineering standards while enabling departments to deliver AI solutions aligned with common security and governance practices.
WHAT YOU'LL BE DOING
- Design, build, evaluate, deploy, and operate end-to-end AI/ML systems in production, spanning data preparation, model development, training or fine-tuning, integration, application logic, monitoring, and continuous improvement.
- Architect and build agentic and multi-agent systems, including orchestration, task routing, shared state, tool use, agent handoffs, human oversight, and failure recovery.
- Design and build enterprise knowledge and retrieval systems across structured and unstructured data, using data pipelines, embeddings, hybrid search, reranking, metadata, and access-controlled retrieval.
- Integrate AI solutions with enterprise applications, APIs, databases, data platforms, and governed tools.
- Establish automated testing, evaluation, and observability practices covering task success, model and retrieval quality, hallucination risk, tool execution, safety, latency, cost, drift, and regression.
- Design secure and responsible AI systems with least-privilege access, auditability, sensitive-data protection, and safeguards against prompt injection, data leakage, and unauthorized actions.
- Create reusable architectures, libraries, and engineering standards, and provide cross-functional technical leadership through design reviews, mentoring, and stakeholder collaboration.
- Evaluate emerging Large Language Models, frameworks, and platforms and make evidence-based adoption recommendations.
QUALIFICATIONS, SKILLS, AND COMPETENCIES
WHAT WE'RE LOOKING FOR
- 8+ years across software engineering and AI/ML, including 3+ years building and operating AI/ML systems in production at scale.
- Strong software engineering skills, particularly in Python or comparable backend technologies.
- Experience developing, adapting, fine-tuning, evaluating, deploying, and monitoring AI or machine learning models.
- Applied AI experience in enterprise use cases such as chatbots, workflow automation, RAG, intelligent document processing, recommendation systems, or decision support.
- Strong understanding of generative AI, LLMs, retrieval systems, agent-based architectures, and applied machine learning.
- Experience with production data pipelines, APIs, model-serving infrastructure, testing, security, reliability, and observability.
- Ability to explain complex technical decisions and tradeoffs to engineering teams and business stakeholders.
NICE TO HAVE
- Experience with agent and workflow orchestration tools such LangGraph, Semantic Kernel, AutoGen, CrewAI, or equivalent.
- Experience with vector databases, semantic or hybrid search, embeddings, and reranking.
- Experience with platforms such as Databricks, Snowflake, Amazon Bedrock, Microsoft Foundry/Azure AI, or equivalent.
- Familiarity with MCP, A2A, self-hosted or open-weight models, and hybrid AI architectures.
WHAT YOU CAN EXPECT
When you choose a career with Safe Software, you’re also choosing…
- Meaningful Work: Make a profound impact across our business, workplace and data integration product.
- A Supportive Environment: Feel empowered to share your ideas and implement them with high autonomy and team support.
- Social Responsibility: Become part of a team that finds meaningful ways to give back https://www.safe.com/about/community-initiatives/. Take paid time off to volunteer for one of our Safe-organized opportunities that align with our core community initiatives.
- Learning & Career Development: We believe in your continuous learning and growth. Take advantage of an annual learning budget and training programs paid for by Safe.
- Flexible Working Hours: Flexible and remote-friendly work arrangements to fit your lifestyle. Work when you want, and how you want to.
- Work-Life Balance: There's no place for burnout at Safe. Maintain a healthy balance of your personal and work life without splitting yourself in two. Enjoy 3 weeks of vacation to recharge, plus an additional paid 6 seasonal days off per year.
- Health & Wellness: Extended health, dental, health or lifestyle spending, and counseling benefits from day 1. That’s right, no waiting period.
- Family is important: We are dedicated to supporting our employees through parenthood and offer a Parental Leave Top-Up Program for new parents through childbirth or adoption.
- Shared Success: Share in Safe’s success with our bi-annual profit sharing and RRSP/TFSA matching program.
- An Accessible Commute: Regardless of your commute method, we’re located close to public transit, and provide complimentary parking and bike storage for our team!
ABOUT SAFE SOFTWARE
Safe Software transforms organizations with FME, the only All-Data Any-AI Enterprise Integration Platform connecting all your data, anywhere, at any velocity.
With over 30 years of expertise and 25,000+ enterprise customers across 125+ countries, we simplify your data journey, wherever it leads.
Founded in 1993, Safe is headquartered in Surrey, BC with over 300 team members and counting. We’re always looking for talented individuals with diverse backgrounds who are determined to learn and grow. Are you ready to join the team?
OUR COMMITMENT TO DIVERSITY AND INCLUSION
Safe Software is an equal opportunity employer and we truly believe that innovation and strength begin with diversity and inclusion.
We welcome all candidates regardless of race, gender identity or expression, sexual orientation, age, ability, disability, national or ethnic origin, political belief, religion, or family status.
Should you require accommodations during the recruitment process, please contact hr_dept@safe.com.
NOTICE REGARDING USE OF AUTOMATED TOOLS IN HIRING
At Safe Software, we use automated tools to help us process applications and identify qualified candidates. These tools may assist in screening resumes and summarizing interview content based on the information you provide. This helps our team review applications efficiently while ensuring every candidate is considered based on the requirements of the role.
Please be assured that the final hiring decision is always made by a member of our team. For more information on how we protect your privacy, please see our policy https://www.safe.com/legal/#applicant-privacy-policy. If you have questions about this process, please contact us at hr_dept@safe.com.
Location: Remote - United States
Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit
www.redditinc.com
.
The
Reddit Consumer Engineering
organization builds and scales the products that Redditors use directly to discover content, participate in communities, and connect with others. Sitting at the intersection of large-scale distributed systems and core user journeys, Product Frontend Engineers in Consumer Engineering partner directly with Product Managers, Designers, Data Scientists, ML Engineers, and Frontend Engineers to build, experiment with, and scale features that power how hundreds of millions of users discover, join, navigate, and engage with Reddit.
This centralized role hires across several high-impact consumer teams, including:
Core Product & Feeds:
Home Experience, Recommendations & Content Discovery, Contribution
Community & Presence:
Reddit Pro, Youth Experience & Teen Safety, Creator Tools
Growth & Engagement:
Authentication, Notifications, Social Sharing, SEO, Onboarding.
Monetization & Conversion:
Paid User Acquisition, Conversion Funnel Optimization
Identity & Security:
Account Management, Trust & Safety
What You’ll Do
Product & Engineering Execution:
Partner closely with cross-functional partners in product, design, and platform engineering to execute on product strategy and build novel, user-centric media features.
Full-Lifecycle Development:
Drive the complete development lifecycle—from technical design and architectural proposals to implementation, unit/integration testing, experimentation, performance analysis, and deployment.
Quality & Velocity:
Move fast while maintaining high quality standards through thorough code reviews, detailed design doc evaluations, and constructive feedback on product specs and UI mocks.
Mentorship & Engineering Standards:
Help establish developer workflows, champion best practices, and mentor junior and mid-level engineers to elevate technical excellence across the team.
Who You Are
Product-Minded Engineer:
You bridge the gap between technical metrics and user experience, understanding how low-level optimizations impact real-world user engagement and product quality.
Pragmatic Builder:
You strike the right balance between rapid iteration and architectural rigor, delivering scalable solutions without getting bogged down by unnecessary processes.
Effective Collaborator:
You excel in communicating complex technical concepts clearly to both technical and non-technical stakeholders.
Continuous Learner:
You have a deep curiosity for emerging technologies and actively keep up with modern industry trends, standards, and performance optimizations.
Technical Qualifications
Frontend Expertise:
Strong proficiency in modern web stacks, including JavaScript, TypeScript, React, and Next.js, with a proven track record of translating complex designs into responsive, production-grade applications.
API & System Design:
Demonstrated experience designing, building, and maintaining robust APIs using protocols such as REST, GraphQL, gRPC, HTTP, or Thrift basics.
Education:
Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience.
Benefits:
Comprehensive Healthcare Benefits and Income Replacement Programs
401k with Employer Match
Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
Family Planning Support
Gender-Affirming Care
Mental Health & Coaching Benefits
Flexible Vacation & Paid Volunteer Time Off
Generous Paid Parental Leave
#LI-remote
Pay Transparency:
This job posting may span more than one career level.
In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit
https://www.redditinc.com/careers/
.
To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.
The base salary range for this position is:
$190,800
—
$267,100 USD
In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.
During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our
Candidate Privacy Policy for Potential Employees and Contractors
.
Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.
Location: Ukraine
OUR HIRING PROCESS:
We will review your application against our job requirements. We do not employ machine learning technologies during this phase as we believe every human deserves attention from another human. We do not think machines can evaluate your application quite like our seasoned recruiting professionals—every person is unique. We promise to give your candidacy a fair and detailed assessment.
We may then invite you to submit a video interview for the review of the hiring manager. This video interview is often followed by a test or short project that allows us to determine whether you will be a good fit for the team.
At this point, we will invite you to interview with our hiring manager and/or the interview team. Please note: We do not conduct interviews via text message, Telegram, etc. and we never hire anyone into our organization without having met you face-to-face (or via Zoom). You will be invited to come to a live meeting or Zoom, where you will meet our INFUSE team.
From there on, it’s decision time! If you are still excited to join INFUSE and we like you as much, we will have a conversation about your offer. We do not make offers without giving you the opportunity to speak with us live.
INFUSE is committed to complying with applicable data privacy and security laws and regulations. For more information, please see our
Privacy Policy
We're looking for Senior AI Engineers to design, build and run LLM-powered agents and AI features in production. You'll work across the full lifecycle: from scoping a use case with stakeholders, through architecture and development, to deployment, evaluation and ongoing improvement.
This is a hands-on role for engineers who think like product owners: you understand the business problem, define what success looks like in numbers, ship to real users, and own the result after launch.
Our stack: Python and TypeScript/Node.js, PostgreSQL, Kafka, Docker, GitHub Actions, AWS. We run multiple LLM providers (Anthropic, OpenAI, Google, AWS Bedrock and others) behind a shared LLM gateway, with MCP for tool access. We work AI-native: agentic coding tools are part of how engineering gets done here, and we provide official Anthropic Claude certification for our engineers.
As part of our team, your responsibilities in this role will include:
Design and build LLM agents and agentic workflows: tool use via MCP, structured outputs, retrieval (RAG), multi-step orchestration, human review steps where needed.
Build and maintain MCP servers and tool layers that give agents governed access to company data and systems.
Own quality and cost: evals and golden sets, per-agent telemetry (tokens, cost, latency, accuracy), prompt and model versioning, provider failover and model routing.
Ship through CI/CD like any other production service: tests and evals in the pipeline, containerized deploys, monitoring, rollbacks.
Contribute to shared platform pieces: the agent template, the LLM gateway, observability.
Work directly with business stakeholders to scope, prioritize and validate use cases. Push back when something doesn't need an agent.
Use AI coding tools daily. Claude Code is our default; deep experience with a comparable agentic tool also works. You drive the tool, verify its output and catch its mistakes.
Our ideal candidate possesses the following skills:
5+ years of software engineering experience, with production systems you've designed, shipped and supported.
Proven experience building LLM-based agents or agentic workflows that reached production with real users.
Hands-on experience with agent frameworks and SDKs: Claude Agent SDK, Claude Managed Agents, Pydantic AI, LangGraph or similar. You can also explain what you'd build without one.
Hands-on experience with MCP and RAG: you've built MCP servers or equivalent tool layers, and retrieval pipelines over real, messy data.
Experience with multiple LLM providers and with AWS Bedrock: model selection, routing, fallbacks, cost and rate-limit management.
Strong Python and SQL. Comfortable in TypeScript/Node.js.
Solid production engineering on AWS: Docker, CI/CD, testing, observability.
Product thinking and business focus: you start from the problem and its cost, define success in measurable terms, and own outcomes.
Daily use of agentic coding tools (Claude Code, Codex, Cursor or similar), with the judgment to verify what they produce.
Clear communication with technical and non-technical stakeholders, in English.
Nice to have:
LLM observability or gateway tooling (Langfuse, LiteLLM, OpenTelemetry for LLM traces or similar).
B2B contact and company data: enrichment, deduplication, matching.
Cloud operations or FinOps: monitoring, incident handling, cost management.
Event-driven or workflow-engine experience (Kafka, Temporal or similar).
Experience replacing no-code or workflow-tool automations with production code.
What we offer:
Fully remote work format;
A collaborative and creative environment that values initiative and experimentation;
Paid time off and sick leave;
Reduced working hours on Fridays during the summer;
Days-off on US national holidays + your birthday;
Schedule: 14 PM - 23 PM EEST (Kyiv time).
Location: Americas Remote
Hi, I'm Paul, VP of Engineering at
Customer.io
. We're looking for a staff engineer to set technical direction for the systems that move billions of messages a day. This isn't a role about shipping more, faster. It's about deciding what gets built, where the architecture needs to go next, and raising the ceiling for the engineers around you.
About
Customer.io
Over 9,000 companies — from scrappy startups to global brands — use our platform to send billions of emails, push notifications, in-app messages, and SMS every day.
Customer.io
powers automated communication that people actually want to receive.
We help teams send smarter, more relevant messages using real-time behavioral data. Under the hood: Go, React, Ember and AI help us ship fast and scale with confidence.
What We Value
Ownership at company scale
You take on the problems nobody has claimed yet — the ones that span squads, have no obvious owner, and would quietly cost us a year if left alone. You either solve them or get leadership aligned to.
Engineers with product taste
You think like a user, not just an engineer. You connect architectural decisions to what customers actually experience, and you can explain that connection to people who don't write Go.
A healthy skepticism for "the way things are done"
You retire practices that have outlived their usefulness, including ones you helped build. Best practices matter — but never more than forward motion.
Force multiplication
Your best quarter isn't measured by what you shipped. It's measured by what the department can now do that it couldn't before.
What You'll Do
Shape the technical direction of our distributed messaging systems in Go — making the high-level architectural calls on mission-critical services where scale, cost, and reliability are all in tension
Take on ambiguous, high-stakes problems that cross squad and function boundaries, and drive them to a decision when the right answer isn't obvious to anyone yet
Build consensus on contested technical questions across teams, and communicate the tradeoffs clearly enough that senior leadership can act on them
Raise the department's bar — set quality and design standards, mentor senior engineers, and turn what you know into frameworks and documentation other teams can use without you in the room
Drive engineering process and tooling improvements that span multiple squads, not just your own
Participate in an on-call rotation as required, supporting the reliability of the systems you build
Interview and calibrate against our career ladder, giving honest, evidence-based assessments of candidates
Use AI agents to make multi-file changes by scoping the work, writing the prompt, and verifying the output
What we're looking for
10+ years building scalable, distributed systems in Go (or similar statically typed languages), including several as the person others turned to on architecture
Depth across multiple systems or domains, not just one — you've been the recognized expert in more than one place
A track record of designing for production reality: you quantify tradeoffs in throughput, cost, and reliability rather than picking a reasonable path and defending it
Experience designing observability and recovery as first-class concerns — metrics, alerting, rollback, backpressure, checkpointing — not logging added afterward
Comfort working in cloud-native environments (AWS, GCP), with relational databases (we use MySQL) and a real understanding of performance tradeoffs
Evidence of making other engineers better: mentorship, technical writing, design review, standards that outlasted your involvement
A bias for action over perfection, and the judgment to know which decisions are worth slowing down for
Compensation & Benefits
We believe in transparency. Starting salary for this role is $200,000 - $240,000 USD (or equivalent in local currency) depending on experience and subject to market rate adjustment. This role also carries a 10% annual bonus target. In addition to base salary, this role includes an equity grant in the form of stock options, so you share in the success you help build.
We know our people are what make us great, and we're committed to taking great care of them. Our inclusive benefits package supports your well-being and growth, including 100% coverage of medical, dental, vision, mental health, and supplemental insurance premiums for you and your family. We also offer 16 weeks paid parental leave, unlimited PTO, stipends for remote work and wellness, a professional development budget, and more.
See full benefits here →
Our Process
No gotchas, no trick questions - just a clear, human process designed to help both of us make an informed decision.
Application
- We review everyone with care. Tell us why you're interested.
Recruiter Call (30 mins)
- Let's chat about what you're looking for and how we work.
Hiring Manager Interview (60 mins)
- Talk with one of our hiring managers about your working style and a project you've owned end-to-end, plus a short AI-assisted coding exercise.
Architecture Interview (60 mins)
- A collaborative system design conversation focused on scaling challenges, tradeoffs, and failure modes.
Take-Home Assignment
- Complete a short, realistic task similar to what you'd work on here.
Assignment Review Call (60 mins)
- Walk us through your work and discuss tradeoffs, priorities, and how you'd iterate.
All final candidates will be asked to complete a background check and employment verifications as part of our pre-employment process.
Customer.io
recognizes the stifling impact of systemic injustice on diverse communities. We commit to using our influence to increase inclusion and equity within the tech industry. We strive to build an inclusive team culture, implement bias-free hiring practices, and develop community partnerships to expand our global impact.
Zoom is the only video conference platform that we use, virtual interviews will be conducted using the video capability (i.e., not via the chat), and offers will be extended in writing on official
Customer.io
letterhead. Please be vigilant in all of your job search activity, and if you have any questions please contact
jobs@customer.io
.
Join us!
We believe in empathy, transparency, responsibility, and, yes, a little awkwardness. If you're excited by what you read and want to build software that makes communication better for everyone—apply now.
Location: Remote - United States
Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit
www.redditinc.com
.
The
Reddit Consumer Engineering
organization builds and scales the products that Redditors use directly to discover content, participate in communities, and connect with others. Sitting at the intersection of large-scale distributed systems and core user journeys, Product Backend Engineers in Consumer Engineering partner directly with Product Managers, Designers, Data Scientists, ML Engineers, and Frontend Engineers to build, experiment with, and scale features that power how hundreds of millions of users discover, join, navigate, and engage with Reddit.
This centralized role hires across several high-impact consumer teams, including:
Core Product & Feeds:
Home Experience, Recommendations & Content Discovery, Contribution
Community & Presence:
Reddit Pro, Youth Experience & Teen Safety, Creator Tools
Growth & Engagement:
Authentication, Notifications, Social Sharing, SEO, Onboarding.
Monetization & Conversion:
Paid User Acquisition, Conversion Funnel Optimization
Identity & Security:
Account Management, Trust & Safety
What You’ll Do
Product & Engineering Execution:
Partner closely with cross-functional partners in product, design, and platform engineering to execute on product strategy and build novel, user-centric media features.
Full-Lifecycle Development:
Drive the complete development lifecycle—from technical design and architectural proposals to implementation, unit/integration testing, experimentation, performance analysis, and deployment.
Quality & Velocity:
Move fast while maintaining high quality standards through thorough code reviews, detailed design doc evaluations, and constructive feedback on product specs and UI mocks.
Mentorship & Engineering Standards:
Help establish developer workflows, champion best practices, and mentor junior and mid-level engineers to elevate technical excellence across the team.
Who You Are
Product-Minded Engineer:
You bridge the gap between technical metrics and user experience, understanding how low-level optimizations impact real-world user engagement and product quality.
Pragmatic Builder:
You strike the right balance between rapid iteration and architectural rigor, delivering scalable solutions without getting bogged down by unnecessary processes.
Effective Collaborator:
You excel in communicating complex technical concepts clearly to both technical and non-technical stakeholders.
Continuous Learner:
You have a deep curiosity for emerging technologies and actively keep up with modern industry trends, standards, and performance optimizations.
Technical Qualifications
Frontend Expertise:
Strong proficiency in modern web stacks, including JavaScript, TypeScript, React, and Next.js, with a proven track record of translating complex designs into responsive, production-grade applications.
API & System Design:
Demonstrated experience designing, building, and maintaining robust APIs using protocols such as REST, GraphQL, gRPC, HTTP, or Thrift basics.
Education:
Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience.
Benefits:
Comprehensive Healthcare Benefits and Income Replacement Programs
401k with Employer Match
Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
Family Planning Support
Gender-Affirming Care
Mental Health & Coaching Benefits
Flexible Vacation & Paid Volunteer Time Off
Generous Paid Parental Leave
Pay Transparency:
This job posting may span more than one career level.
In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit
https://www.redditinc.com/careers/
.
To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.
The base salary range for this position is:
$164,200
—
$229,900 USD
In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.
During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our
Candidate Privacy Policy for Potential Employees and Contractors
.
Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.
Location: Mapbox Helsinki
Workplace: Remote
Mapbox is the leading real-time location platform for a new generation of location-aware businesses. Mapbox is the only platform that equips organizations with the full set of tools to power the navigation of people, packages, and vehicles everywhere. More than 4 million registered developers have chosen Mapbox because of the platform’s flexibility, security and privacy compliance. Organizations use Mapbox applications, data, SDKs and APIs to create customized and immersive experiences that delight their customers.
As AI becomes embedded in modern engineering workflows, we value engineers who can thoughtfully integrate AI into design, development, and decision-making. Our interview process will include discussion of how you use AI in your engineering workflow.
WHAT YOU'LL DO
This role is scoped by skill rather than by product. The problems below span multiple departments and show up across our Search and Places data work, our Location and Navigation Intelligence work, and the Platform work that makes Mapbox usable by agents. You'll be hired into one specific team or product area, but you'll work across teams where your expertise meets the highest-priority AI problems. You should expect to move between teams and tech stacks as the work demands.
At this level you own the technical design and delivery of a multi-component AI system, and you are accountable for the quality of what ships in your area.
IN THIS ROLE, YOU WILL:
- Define how the products you own should work, build a measurement framework for it, and build evaluation systems for non-deterministic behavior. Formulate hypotheses around the products we build and seek the signal needed to validate them. Define what a correct result is for a given input and state, determine whether to assemble datasets from real usage or hand-written cases, and gate changes on regression results.
- Run continuous evaluation of the products we build, whether APIs, SDKs, data representations, or reference applications, from the position of the end user, whether developer, agent, or consumer. Assess the gaps such as misuse of parameters or integration anti-patterns, recommend the fixes, and make sure they land.
- Own the MVP against an agreed north star technical design, and balance technical perfection against shipping useful increments.
- Build data pipelines and the tooling around them: ingestion, conflation, entity resolution, quality checks, and the batch and streaming jobs that keep a large dataset current.
- Track and pull external datasets, models, and benchmarks from published research and open-source releases. Evaluate what fits the problem and constraints , and decide when to adopt what exists versus build your own.
- Design feedback loops so that using a product generates data that improves it. Instrument systems so failures arrive with enough context to reproduce, then turn the recurring ones into evaluation cases.
- Design the boundary between a model and the tools it calls. Build or improve the model harness, decide what the model handles, what it delegates, and how to keep it working from the state it actually fetched.
- Work to a latency and cost target per request: streaming, partial results, caching, model routing, prompt structure.
- Build the internal harnesses and tools (CLI, MCP, and others) your team needs to iterate quickly, and share the parts that generalize with other teams.
- Raise the bar on your team through code and design review, and bring other engineers up on eval practice.
- Some of the technical questions in this area are still open. You will help answer them.
- Participate in an on-call rotation to ensure our systems remain available to customers 24/7. Team members alternate as the on-call primary responder, which may require immediate response outside normal working hours, including weekends.
WHAT WE BELIEVE ARE IMPORTANT TRAITS FOR THIS ROLE
- Bachelors degree in STEM discipline and 5+ years of software engineering experience, with production ownership of services, pipelines, or SDKs.
- 2+ years shipping LLM-backed features to real users, in systems that carried error budgets, on-call rotations, and customers who noticed regressions.
- Direct experience or deep understanding of designing evaluations for non-deterministic systems. You can describe a dataset you built and the failure it caught.
- Data engineering depth: SQL, at least one distributed processing framework, and experience with pipelines where a wrong record mattered more than a slow one.
- Fluency with tool calling and agent orchestration, including the failure modes: stale context, hallucinated arguments, silent partial success, unbounded loops.
- Working knowledge of more than one agent harness, and opinions about where each of them is weak.
- Strong Python or TypeScript, and comfort reading code in whatever language the caller happens to be written in.
- Experience diagnosing latency in a distributed request path.
- Comfort with ambiguity, and the judgment to ship something narrow that works while the general solution is still unclear.
- Clear written communication. Mapbox is distributed across time zones and we make most decisions in documents and Slack.
NICE TO HAVE TRAITS FOR THIS ROLE
- Geospatial data experience: routing, geocoding, POI or address data, OpenStreetMap, or conflation of overlapping sources.
- Public API or SDK design experience, particularly for developers you never talk to.
- Experience building against MCP or similar tool transports.
- Experience running evals in CI, with a commercial harness or one you built.
- Automotive, in-vehicle infotainment, CarPlay, or Android Auto experience.
- Voice pipeline experience: streaming ASR, TTS, barge-in, endpointing, wake word.
- Work under constrained compute, offline, or intermittent connectivity.
- Experience operating a product through its first external integrations, where the customer finds the gaps before you do.
WHAT WE VALUE
In addition to our core values https://www.mapbox.com/about/values/, which are not unique to this position and are necessary for Mapbox leaders:
- We value high-performing creative individuals who dig into problems and opportunities.
- We believe in individuals being their whole selves at work. We commit to this through supportive health care, parental leave, flexibility for the things that come up in life, and innovating on how we think about supporting our people.
- We emphasize an environment of teaching and learning to equip employees with the tools needed to be successful in their function and the company.
- We strongly believe in the value of growing a diverse team and encourage people of all backgrounds, genders, ethnicities, abilities, and sexual orientations to apply.
HOW WE SUPPORT YOU
- Hybrid/Remote Options: Enjoy flexibility to work comfortably from home or periodically from an office where applicable.
- Country-Specific Care & Coverage: Private health, dental, and income protection plans tailored to elevate your regional statutory benefits.
- Family-First Support: Family care, maternity and paternity leave policies to support your growing family.
- Lifestyle Spending Account: Contributions to support your health, wellness, and personal growth
- Balance & Brainpower: Mental health support for you and your dependents.
- Rest & Recharge: Paid time away, company holidays, and generous absence policies.
- Time Off to Give Back: Dedicated paid volunteering time in addition to your standard PTO.
By applying for this position, you acknowledge that you have received the Mapbox Non-US Privacy Notice https://www.mapbox.com/legal/applicant-privacy-notice/ for applicants, which is linked here. Completing this application requires you to provide personal data, such as your name and contact information, which is mandatory for Mapbox to process your application.
We are committed to a fair and equitable hiring process. We do not discriminate against any protected class.
#LI-Remote
Location: San Francisco, CA; New York, NY
Workplace: OnSite
ABOUT US
Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia.
We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do.
Sierra was co-founded by Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/ who first met while working together at Google over 20 years ago. Bret currently serves as Chairman of the Board of Open AI. Previously, he was co-CEO of Salesforce and CTO of Facebook. Clay spent 18 years at Google, where he most recently led Google Labs.
WHAT YOU’LL DO
As an Agent Strategist https://sierra.ai/blog/agent-strategist-your-phd-in-applied-ai, you own how Sierra’s AI agents come to life for our customers — from first pilot to a production agent handling thousands of conversations a day. You sit at the intersection of product, building agents and customer-facing work, and stay just as close to the technology as you are to the people you build for. You transform a customer’s thorniest, highest-stakes problems into agents that measurably move their business.
- Own the Agent Development Life Cycle https://sierra.ai/blog/agent-development-life-cycle. Take agents from initial scope through conversation design, tooling, and evaluation, to launch and continuous iteration in production — translating business goals into an agent that outperforms, and tuning relentlessly until it’s the best version of itself in the real world. You’ll have real ownership and autonomy over the outcome.
- Be the trusted strategic advisor to enterprise leaders. Sit shoulder-to-shoulder with our customers’ executives, understand what success actually means to their business, and shape the AI strategy that gets them there.
- Partner with the customer’s working teams day to day. Run working sessions, troubleshoot the agent as issues come up, and make the calls that keep the build on track for launch.
- Directly impact product. Surface unmet needs from your customer work, and feed them back to research and platform to shape where Sierra goes next.
EXAMPLE PROJECTS
These are the kinds of projects that strategists on our team have worked on recently:
- Scope and launch a subscription-retention agent for a large telecommunications or media company that consistently outperforms human agents at saving at-risk customers.
- Stand up an agent for a commerce customer that troubleshoots a broken device end-to-end and personalizes product recommendations in the same conversation.
- Redesign the conversation flows for a financial services agent so it can handle complex, regulated interactions — and convert a pilot into a multi-team production deployment. See our financial services blog https://sierra.ai/blog/five-ways-to-use-ai-agents-financial-services for examples.
- Partner with product on a net-new capability — a new agent architecture or self-service tooling — using a live customer as the design partner.
- Define the evaluation and quality bar for a new agent, then use those metrics to drive a measurable lift in outcome https://sierra.ai/blog/outcome-based-pricing-for-ai-agents week over week.
WHAT YOU’LL BRING
- Customer obsession. Genuine energy being in front of customers — understanding their business and needs, thriving in complex organizations, and building trusted relationships.
- Communication. Clear, direct, and persuasive across technical and non-technical audiences.
- Strategic problem-solving in ambiguity. Strong analytical and critical-thinking skills to break down complex problems, spot risks early, and adapt as things change fast.
- Technical aptitude. Comfortable engaging directly with technical concepts - reading API documentation, understanding data models and system architecture, and following engineering tradeoffs in a design discussion.
- Ownership and delivery. A track record of running multiple complex, high-visibility projects at once and driving them to outcomes.
- Genuine interest in Financial Services and improving the end customer experience. Experience in financial technology, implementations at financial institutions, working inside of these institutions or familiarity with financial services security and compliance requirements (fair lending, PII handling, etc.) are a strong plus.
EVEN BETTER...
- Experience building or deploying AI/LLM agents in production — hands-on with the tools behind them (eval frameworks, agent tooling, RAG, prompt engineering) — working closely with technical counterparts.
- You’ve been a founder, founding team member, or operator — you know how to balance craft, ownership, and speed.
- A degree in Computer Science, Engineering, Mathematics, a related technical field, or equivalent practical experience — and/or an MBA or comparable experience at the intersection of technology and business.
OUR VALUES
- Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work.
- Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it.
- Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve.
- Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time.
- Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements.
WHAT WE OFFER
We want our benefits to reflect our values and offer the following to full-time employees:
- Flexible (unlimited) paid time off
- Medical, dental, and vision benefits for you and your family
- Life insurance and disability benefits
- Retirement plan dependent on country of employment
- Parental leave
- Fertility and family building benefits
- Lunch, as well as delicious snacks and coffee to keep you energized when working onsite
- Discretionary benefit stipend giving people the ability to spend where it matters most
- Free alphorn lessons
These benefits are further detailed in Sierra's policies, may vary by region and employment type, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies.
BE YOU, WITH US
We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply through the link on this page even if your experience doesn't precisely match the job description.
Sierra is a proud equal opportunity employer. All qualified applicants will receive consideration for employment without regard to any characteristic protected by applicable federal, state or local laws, including veteran status and disability status. Hiring decisions are made by people, based on merit. If you need a reasonable accommodation for a disability, a religious practice, pregnancy or any related condition at any point in the application or interview process, contact us at accommodations@sierra.ai. Requests are handled confidentially and do not affect your candidacy.
We will consider qualified applicants with arrest and conviction records in accordance with applicable fair chance laws.
Typeform is a form builder helping over 150,000 businesses collect data with forms, surveys, and quizzes. The company is fully remote and hires candidates based in the UK, Ireland, Germany, Portugal, or The Netherlands.
Product Operations is central to how Product and R&D teams work, creating systems and practices to focus on solving the right problems and delivering products. AI is increasingly important, with teams experimenting with tools like Glean and Claude, automations, agents, and AI usage throughout product development.
The role of AI Product Operations Lead involves building and operating internal AI Operations capability for R&D. It requires turning ambiguous opportunities into reliable solutions by identifying high-value AI problems, understanding workflows, designing solutions, building or coordinating delivery, and being accountable for performance after launch.
Responsibilities include:
— Building and improving a backlog of AI opportunities across R&D, prioritizing impactful AI jobs.
— Taking ambiguous problems from discovery to delivery: understanding users and workflows, exploring options, designing systems, implementing, testing, documenting, launching, measuring, and improving.
— Designing simple AI-native solutions fitting naturally into workflows, deciding when prompts, automations, integrations, agents, databases, or custom apps are appropriate.
— Helping R&D get value from enterprise AI tools like Glean and Claude, partnering with IT and InfoSec on access, configuration, connectors, enablement, and support.
— Owning the lifecycle of AI systems including automations, skills, agents, and internal web apps.
— Establishing evaluation, testing, reliability, observability, security, and maintenance practices, improving systems over time.
— Partnering across R&D to uncover needs, unblock delivery, clarify ownership, and involve experts.
— Running and evolving R&D AI governance and enablement practices, providing leaders visibility into work, risks, adoption, and outcomes.
— Participating in broader AI governance efforts as an R&D contributor.
— Working with Finance and partners to improve visibility into AI tool usage, spend, and value to inform investments.
— Exploring and supporting autonomous agents to improve planning, discovery, design, build, evaluation, and management across product development.
Requirements:
— Strong practical experience applying AI to real-world problems, building usable solutions.
— Proven track record taking ambiguous problems from discovery through implementation, testing, adoption, and improvement.
— Excellent systems thinking to understand people, processes, tools, data flows, integrations, permissions, and constraints, making trade-offs.
— Strong user and workflow discovery skills to understand real jobs and simplify solutions.
— Hands-on technical fluency building, modifying, troubleshooting internal workflows, automations, agents, or apps.
— Practical experience with modern development tools like GitHub, repositories, pull requests, application hosting, deployment, logging, and troubleshooting.
— Ability to manage work independently: prioritizing backlog, handling dependencies and risks, documenting decisions, communicating with stakeholders.
— Strong approach to evaluation and reliability, defining "good", testing, collecting feedback, and improving live systems.
— Ability to work effectively across technical and non-technical teams, asking questions, challenging assumptions, seeking expert input, and progressing without close supervision.
— Good judgment on responsible AI, security, access, governance, and knowing when to involve partners.
The role reports to VP of Product Operations and collaborates with Product, Engineering, Design, Research, Data Science, IT, InfoSec, and AI practitioners across Typeform.
Задачи:
• Формировать AI-стратегию и roadmap бизнес-направления.
• Находить наиболее перспективные точки применения AI.
• Самостоятельно запускать первые прототипы и AI-пилоты.
• Быстро проверять гипотезы и показывать первые измеримые результаты.
• Создавать AI-агентов, RAG-решения и AI-автоматизации.
• Формировать и приоритизировать портфель AI-инициатив.
• Совместно с FDE и AI-командой доводить успешные пилоты до production и масштабирования.
• Переосмысливать бизнес-процессы с учетом возможностей AI.
• Работать с руководителями бизнес-направлений и защищать AI-инициативы.
• Следить за развитием AI-технологий и применять новые подходы в реальных бизнес-кейсах.
Требования:
• 7+ лет профессионального опыта в технологиях, AI/ML, разработке продуктов или digital transformation.
• Практический опыт запуска AI/ML или технологических продуктов.
• Сильное понимание LLM, Generative AI, AI Agents и RAG.
• Способность самостоятельно собрать работающий AI-прототип.
• Product mindset и ориентация на быстрый результат.
• Стратегическое мышление и способность формировать AI-roadmap.
• Умение связывать технологии с конкретным бизнес-эффектом.
• Опыт работы с руководителями и топ-менеджментом.
• Высокая самостоятельность и ответственность за результат.
AI-инструменты и технические навыки:
• Практический опыт работы с OpenAI, Claude, Gemini, Llama, Qwen или аналогичными LLM.
• Работа с LLM API, Prompt Engineering, Tool/Function Calling.
• Создание AI-агентов с использованием LangChain, LangGraph, LlamaIndex или аналогов.
• Практическое понимание RAG, embeddings, vector databases.
• Использование AI coding-инструментов: Codex, Cursor, Claude Code или аналогов.
• Python, REST API, SQL — на уровне, достаточном для самостоятельного создания прототипов.
• Опыт работы с n8n, Make или другими инструментами автоматизации.
• Понимание принципов работы и ограничений LLM, стоимости моделей и вопросов безопасности корпоративных данных.
Кого мы ищем:
• Не классического бизнес-аналитика или координатора.
• Нужен человек, который способен: понять бизнес → увидеть возможность применения AI → самостоятельно собрать первый пилот → показать результат → сформировать roadmap → масштабировать решение вместе с командой.
Главный результат:
• Быстрые первые победы и последующая системная AI-трансформация бизнес-направления.
Location: Efkarpia, Greece; Athens, Greece
Join the Alumil Team as a Project Engineer!
Alumil, a leading manufacturer of architectural aluminum systems, is looking for a dedicated Project Engineer to join our dynamic Sales team. This role will involve collaborating with various departments & stakeholders to ensure the successful completion of projects while maintaining our high standards of quality and innovation.
The Role
The Project Engineer plays a vital role in the International Projects Department. This position is designed to serve as a technical advisor for the company’s global initiatives, leveraging specialized calculation software and CAD tools to provide support to customers and the Group’s subsidiaries.
You will coordinate with internal stakeholders, including design, R&D, manufacturing, and sales teams, while also liaising with clients to ensure their specifications and expectations are met. As a Project Engineer, you are responsible to provide project based technical support to customers and subsidiaries.
Your key responsibilities will include:
Plan and manage project schedules, budgets, and resources.
Conduct engineering calculations and analyses to support project development.
Review and approve design plans and specifications.
Ensure adherence to industry standards, regulations, and safety protocols.
Communicate project status and updates to all stakeholders.
Identify and mitigate project risks and issues throughout the life cycle of the project.
Assist in the preparation of engineering documentation and reports.
Collaborate with the sales team to provide technical support during the bidding phase.
Conducts research and determines the specifications and requirements for international projects.
Enables the seamless export of construction drawings using AutoCAD to support our international projects.
Maintains the Customer Relationship Management (CRM) system by ensuring that all pertinent information related to each project is promptly updated.
Support and communicate with the customers to identify their needs.
Requirements
A degree in Engineering or a related discipline from a university or technical institute, such as Mechanical, Civil, Architecture, or other relevant fields of study.
Demonstrated experience of at least 2 years in project engineering
Expertise in aluminum and construction fields will be highly valued.
Proficiency in AutoCAD and other engineering design software.
Familiarity with Rhino or REVIT is a plus.
Professional experience with static analysis software (such as SCIA, RFEM, etc.) would be considered a plus.
Strong analytical and problem-solving skills.
Excellent communication and interpersonal skills.
Ability to work independently and as part of a team.
Fluency in English; knowledge of additional languages is a plus.
Benefits
Provision of private life & health insurance
Annual performance bonus
Work equipment & tools
Annual customized training plan
ALUMΙL opposes any discrimination, unequal treatment and violation of human rights and ensures the provision of equal opportunities at work. When hiring and evaluating employees, it does not discriminate based on race, gender, religion, age, disability, sexual orientation, nationality, political beliefs or social status.
ALUMIL complies with the statutory provisions strengthening the application of the principle of equal pay for men and women for equal work or work of equal value (Law 5316/2026). The selection process is gender-neutral, and recruitment procedures are conducted in a non-discriminatory manner. Candidates are assessed solely on the basis of objective, job-related criteria.
Every candidate has the right to be informed, in writing or orally, of the pay range for the position prior to the job interview. The pay range has been determined on the basis of objective, gender-neutral criteria, free of any other form of discrimination, in accordance with the company’s pay structure.
Location: Remote - United States
Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit
www.redditinc.com
.
Team Description:
The Ads Retrieval ML team builds the machine learning systems that identify relevant advertising candidates for Reddit users. Retrieval sits at the heart of the ads delivery funnel: before downstream ranking and auction decisions, our models determine which campaigns and ads are eligible to compete. We work on large-scale retrieval across multiple objectives, placements, and geographies. Our work combines representation learning, candidate generation, nearest-neighbor search, behavioral and contextual signals, and rigorous offline and online experimentation.
Role Description:
We are looking for a Staff Machine Learning Engineer to provide technical leadership for the Retrieval ML team. You will lead the design and evolution of retrieval models and modeling practices that improve relevance, advertiser outcomes, and user experience at Reddit scale. This is an applied ML role centered on retrieval modeling and end-to-end product impact. You will be expected to stay close to the technical details—from data and objective design through model development, evaluation, experimentation, and launch—while setting direction for other engineers.
Responsibilities:
Define the technical direction and multi-year roadmap for ads retrieval modeling in partnership with engineering, product, data science, and ads stakeholders.
Design, develop, and launch candidate-generation and retrieval models for campaigns and ads across Reddit’s advertising surfaces.
Apply modern approaches such as two-tower architectures, representation learning, embeddings, sequence models, graph-based methods, and other deep learning techniques when they create meaningful product value.
Improve the retrieval stack across key modeling decisions, including objectives, labels, sampling strategies, hard-negative mining, feature design, embedding generation, candidate filtering, and retrieval depth.
Work with approximate nearest-neighbor and vector retrieval systems, reasoning about recall, relevance, freshness, diversity, coverage, latency, and cost trade-offs.
Establish strong evaluation practices that connect retrieval metrics—such as recall, precision, candidate coverage, calibration, and downstream lift—to ads and user outcomes.
Lead offline analysis and online experiments, interpret ambiguous results, and translate findings into the next modeling iteration.
Partner with downstream ranking, ads platform, auction, measurement, and product teams to ensure retrieval models integrate effectively into the full ads funnel.
Write design documents, review code and model changes, and raise the quality bar for modeling, testing, observability, and production ownership.
Mentor ML engineers and help grow the team’s expertise in retrieval, recommendation, and representation learning.
Required Qualifications:
7+ years of industry experience, including substantial experience building and shipping applied ML products.
Deep experience with information retrieval, candidate generation, recommender systems, ranking, or related relevance problems.
Strong understanding of retrieval modeling concepts, including DNN, embeddings, two-tower or dual-encoder models, approximate nearest-neighbor search, and multi-stage retrieval.
Deep experience training, evaluating, debugging, and deploying deep learning models using TensorFlow, PyTorch, or similar frameworks.
Demonstrated ownership of ML projects from problem framing and data preparation through offline evaluation, online experimentation, production launch, and iteration.
Strong command of experimental design and model evaluation, including how offline retrieval metrics relate to downstream business and user metrics.
Experience working with large-scale behavioral, contextual, or content datasets and complex feature pipelines.
Strong software engineering fundamentals and the ability to write clear, reliable, maintainable production code.
Technical leadership experience: setting direction, leading complex projects, influencing partner teams, and mentoring other engineers.
Excellent written and verbal communication, with the ability to explain complex modeling choices to technical and non-technical audiences.
Preferred Qualifications:
Experience with ads retrieval, ad serving, recommendation, search relevance, or marketplace optimization
Experience modeling user, content, campaign, or ad interactions with sequential, graph, or multimodal signals
Experience connecting retrieval improvements to downstream ranking, auction, conversion, revenue, or user-experience outcomes
Experience in ads marketplaces at peer companies
Publications, patents, or industry contributions in applied ML or ranking systems
Experience with sequential modeling (e.g., RNNs, Transformers)
Benefits:
100% remote opportunity (we have 4 office locations for hybrid/onsite work preference in NY, SF, LA and Chicago)
Comprehensive Healthcare Benefits and Income Replacement Programs
401k with Employer Match
Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
Family Planning Support
Gender-Affirming Care
Mental Health & Coaching Benefits
Flexible Vacation & Paid Volunteer Time Off
Generous Paid Parental Leave
#LI-AJ1
Pay Transparency:
This job posting may span more than one career level.
In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit
https://www.redditinc.com/careers/
.
To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.
The base salary range for this position is:
$230,000
—
$322,000 USD
In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.
During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our
Candidate Privacy Policy for Potential Employees and Contractors
.
Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.
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