This means driving deployments from scoping through production, running the platform work that spans them, and working across API, Platform Foundations, Security, our cloud provider counterparts, and whoever else is on the critical path when dependencies and tradeoffs pile up.

Responsibilities:

• Own end-to-end program execution for Anthropic’s API across major cloud deployments, from scoping through production launch and steady-state operations

• Drive the platform programs that cut across individual deployments: the shared foundations that get built once and reused, not rebuilt per cloud

• Act as a primary coordination point with cloud provider counterparts, keeping engagement clean across multiple internal teams with touchpoints into the same partner

• Partner with engineering leadership to turn technical direction into executable plans with clear owners, dependencies, and risk tracking

• Build the program scaffolding (roadmaps, status reporting, decision logs, escalation paths) that lets a fast-moving org stay aligned without slowing down

• Drive the hard sequencing conversations when partner commitments, engineering bandwidth, and priorities are in tension, and surface them to leadership with a recommendation

• Identify where program coverage is thin relative to the load and help shape how we staff around it

You may be a good fit if you:

• Have 10+ years of technical program management experience, including ownership of large infrastructure or platform programs with many engineering teams and external partners in the mix

• Have deep technical fluency in cloud APIs, infrastructure, distributed systems, or platform engineering, enough to be a credible partner to senior engineers on architecture and sequencing, not just a tracker of their decisions

• Have run programs spanning organizational boundaries where you had no direct authority over most of the people whose work you depended on, and delivered anyway

• Have direct experience with multi-cloud or hybrid cloud environments, large-scale migrations, or building platform abstraction layers

• Have worked with major cloud providers (AWS, GCP, Azure) or similar large technology partners, and know how to keep those relationships productive when priorities diverge

• Are comfortable operating in ambiguity on the long arc while being ruthlessly concrete on what ships this quarter and who owns it

• Have a track record of making a program get cheaper to run the second and third time, not just landing the first instance

• Thrive in environments where the plan you wrote last month needs rewriting, without losing the thread on what matters

Strong candidates may also:

• Have experience with production serving infrastructure, inference systems, or ML platform work

• Have moved between senior IC and management roles, or have interest in doing so

• Have worked at a company rebuilding systems and org in flight during rapid scale-up

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Anthropic is looking for an Engineering Manager to lead the Agent Prompts & Evals team. This team owns the infrastructure that lets Anthropic ship model and prompt changes with confidence , the eval frameworks, system prompt pipelines, and regression-detection systems that every model launch depends on.

When a new Claude model is ready to ship, this team is the one answering “is it actually better in our products?” When a product team wants to change how Claude behaves, this team owns the tooling that tells them whether they broke something. It’s a platform team whose platform is model behavior itself.

The team sits deliberately at the seam between product engineering and research. You’ll partner closely with other evals groups across the company on shared infrastructure and methodology, with product teams who are shipping features on top of Claude, and with the TPMs and research PMs driving model launches. The pace is set by the model release cadence, and the team operates as both a platform owner and a hands-on partner during launch periods.

Responsibilities

• Lead and grow a team of prompt engineers and platform software engineers
• Own the product-side eval platform: the frameworks, dashboards, bulk runners, and CI integrations that product teams use to measure Claude’s behavior and catch regressions before they ship
• Own system prompt infrastructure: versioning, deployment, rollback, and review tooling for the prompts that run in production across claude.ai, the API, and agentic surfaces
• Be a steady hand through model launches , these are the team’s highest-stakes operational moments and the EM is the backstop when things get chaotic
• Build durable collaboration with other evals groups across the company; this means real work on ownership boundaries, shared roadmaps, and avoiding tragedy-of-the-commons on shared eval infrastructure
• Recruit, close, and retain engineers who want to work at the intersection of product engineering and model behavior
• Shape where the team invests next: there are credible paths into frontier eval development, model launch automation, and deeper prompt engineering support, and part of the job is sequencing them
• Push the team toward measuring things that are hard to measure , behavioral drift, prompt quality, harness parity , not just things that are easy

You May Be a Good Fit If You Have

• 8+ years in software engineering with 3+ years managing engineering teams, including experience leading a platform, infra, or developer-tooling team where your customers were other engineers
• A track record of building “pits of success” , tooling and process that made it easy for other teams to do the right thing without needing to understand all the details
• Comfort managing a team with a mixed charter: platform ownership, service-to-other-teams, and a launch-driven operational rhythm, all at once
• Enough technical depth to engage on system design, review pipeline architecture, and be credible in debates with strong ICs , you don’t need to be writing code by hand every day, but you should be able to read it, review it, and be comfortable leveraging Claude to understand, design, and occasionally build.
• A product mindset and willingness to wear multiple hats when the work calls for it
• Demonstrated ability to build and maintain peer relationships with partner orgs that have different cultures and incentives , negotiating ownership, aligning roadmaps, and holding ground when it matters without being territorial about it
• Experience recruiting and closing senior ICs in a competitive market

Strong Candidates May Also Have

• Prior exposure to LLM evals, ML experimentation platforms, or model quality work , even tangentially
• Experience with A/B testing infrastructure, feature flagging, or gradual rollout systems
• Background in devtools, CI/CD platforms, or testing infrastructure at scale
• A history of managing teams that sit between two larger orgs and making that position an asset rather than a liability
• Interest in AI safety and alignment , not required, but it makes the “why” of the work land harder

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.

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

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This means driving deployments from scoping through production, running the platform work that spans them, and working across API, Platform Foundations, Security, our cloud provider counterparts, and whoever else is on the critical path when dependencies and tradeoffs pile up.

Responsibilities:

• Own end-to-end program execution for Anthropic’s API across major cloud deployments, from scoping through production launch and steady-state operations

• Drive the platform programs that cut across individual deployments: the shared foundations that get built once and reused, not rebuilt per cloud

• Act as a primary coordination point with cloud provider counterparts, keeping engagement clean across multiple internal teams with touchpoints into the same partner

• Partner with engineering leadership to turn technical direction into executable plans with clear owners, dependencies, and risk tracking

• Build the program scaffolding (roadmaps, status reporting, decision logs, escalation paths) that lets a fast-moving org stay aligned without slowing down

• Drive the hard sequencing conversations when partner commitments, engineering bandwidth, and priorities are in tension, and surface them to leadership with a recommendation

• Identify where program coverage is thin relative to the load and help shape how we staff around it

You may be a good fit if you:

• Have 10+ years of technical program management experience, including ownership of large infrastructure or platform programs with many engineering teams and external partners in the mix

• Have deep technical fluency in cloud APIs, infrastructure, distributed systems, or platform engineering, enough to be a credible partner to senior engineers on architecture and sequencing, not just a tracker of their decisions

• Have run programs spanning organizational boundaries where you had no direct authority over most of the people whose work you depended on, and delivered anyway

• Have direct experience with multi-cloud or hybrid cloud environments, large-scale migrations, or building platform abstraction layers

• Have worked with major cloud providers (AWS, GCP, Azure) or similar large technology partners, and know how to keep those relationships productive when priorities diverge

• Are comfortable operating in ambiguity on the long arc while being ruthlessly concrete on what ships this quarter and who owns it

• Have a track record of making a program get cheaper to run the second and third time, not just landing the first instance

• Thrive in environments where the plan you wrote last month needs rewriting, without losing the thread on what matters

Strong candidates may also:

• Have experience with production serving infrastructure, inference systems, or ML platform work

• Have moved between senior IC and management roles, or have interest in doing so

• Have worked at a company rebuilding systems and org in flight during rapid scale-up

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This role is not simply about running programs,it is about designing and scaling the engineering platforms, guardrails, and operating models that make secure and compliant product development the default across a rapidly growing, multi-cloud ecosystem.

As a Director of Engineering, Governance Foundation, you will lead a team of senior security engineers, partner with product and infrastructure leaders, and shape the foundational governance systems that enable Databricks to innovate quickly while maintaining world-class security and customer trust.

Your responsibilities will include:

• Defining the company-wide strategy for embedding security, privacy, and responsible data use across engineering workflows and platform components.

• Building scalable governance frameworks that help engineering teams design secure systems from the start, not after the fact.

• Establishing and leading a Security & Privacy Postmortem Review process that drives learning, accountability, and long-term resilience.

• Ensuring insights from incidents translate into systemic improvements across tools, infrastructure, and engineering culture.

• Rebuilding and scaling a Security Champions Network that brings security and governance expertise directly into product and infrastructure teams.

• Creating centralized enablement, tooling, and shared learning systems that allow thousands of engineers to integrate security seamlessly.

• Leading efforts to ensure responsible data use across AI/ML systems, SaaS environments, and internal workspaces.

• Defining and enforcing policies that uphold privacy, integrity, auditability, and proper data lifecycle management.

• Transforming security into a key enabler for engineering velocity.

• Delivering automation, self-service tools, and intelligent guardrails that reduce developer friction while increasing safety and compliance.

• Building JIT (Just-In-Time) security education and systems that proactively surface risky behaviour before it becomes an incident.

• Identifying and elevating Databricks' security posture to exceed DB50 customer expectations, including areas such as audit logging, controlled access workflows, secure asset import/export, behaviour monitoring and lineage.

• Partnering with security, IT, and compliance teams to ensure readiness for the most demanding enterprise and regulated environments.

To be successful in this role, you will need:

• 10+ years of experience in large-scale software engineering, with at least several years leading engineering managers and senior ICs.

• Strong technical grounding in backend systems, distributed systems, identity/security, or enterprise cloud platforms.

• Experience defining governance, security, or enterprise-grade platform capabilities.

• A background as a senior IC (e.g., Staff/Principal Engineer) at some point,this role requires deep technical credibility.

• Proven success hiring, developing, and retaining senior engineering talent.

• Expertise driving cross-functional technical programs with senior stakeholders.

• Experience building cloud-agnostic or multi-cloud services.

• Background in enterprise features such as access control, policy engines, compliance, or identity systems.

• Experience leading organisations through scaling phases in high-growth environments.

You will be rewarded with a competitive salary range of $255,900-$305,350 USD, plus eligibility for annual performance bonus, equity, and comprehensive benefits.

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We are seeking a highly technical and influential Director of Engineering, Governance Foundation to define how security, privacy, and responsible data practices are built into the core of Databricks' products and infrastructure.

This role is not simply about running programs,it is about designing and scaling the engineering platforms, guardrails, and operating models that make secure and compliant product development the default across a rapidly growing, multi-cloud ecosystem.

Responsibilities

Security & Privacy Governance Architecture

• Define the company-wide strategy for embedding security, privacy, and responsible data use across engineering workflows and platform components.

• Build scalable governance frameworks that help engineering teams design secure systems from the start, not after the fact.

Incident Learning & Prevention

• Establish and lead a Security & Privacy Postmortem Review process that drives learning, accountability, and long-term resilience.

• Ensure insights from incidents translate into systemic improvements across tools, infrastructure, and engineering culture.

Security Champions & Distributed Expertise

• Rebuild and scale a Security Champions Network that brings security and governance expertise directly into product and infrastructure teams.

• Create centralized enablement, tooling, and shared learning systems that allow thousands of engineers to integrate security seamlessly.

Data Governance for Products & AI

• Lead efforts to ensure responsible data use across AI/ML systems, SaaS environments, and internal workspaces.

• Define and enforce policies that uphold privacy, integrity, auditability, and proper data lifecycle management.

Developer-Centric Security Enablement

• Transform security into a key enabler for engineering velocity.

• Deliver automation, self-service tools, and intelligent guardrails that reduce developer friction while increasing safety and compliance.

• Build JIT (Just-In-Time) security education and systems that proactively surface risky behaviour before it becomes an incident.

Security Maturity & Customer Trust

• Identify and elevate Databricks' security posture to exceed DB50 customer expectations, including areas such as:

• audit logging

• controlled access workflows

• secure asset import/export

• behaviour monitoring and lineage

• Partner with security, IT, and compliance teams to ensure readiness for the most demanding enterprise and regulated environments.

Requirements

• 10+ years of experience in large-scale software engineering, with at least several years leading engineering managers and senior ICs.

• Strong technical grounding in backend systems, distributed systems, identity/security, or enterprise cloud platforms.

• Experience defining governance, security, or enterprise-grade platform capabilities.

• A background as a senior IC (e.g., Staff/Principal Engineer) at some point,this role requires deep technical credibility.

• Proven success hiring, developing, and retaining senior engineering talent.

Preferred Qualifications

• Experience building cloud-agnostic or multi-cloud services.

• Background in enterprise features such as access control, policy engines, compliance, or identity systems.

• Experience leading organisations through scaling phases in high-growth environments.

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilising the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.

Local Pay Range $243,100-$290,100 USD

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Anthropic is looking for an Engineering Manager to lead the Agent Prompts & Evals team. This team owns the infrastructure that lets Anthropic ship model and prompt changes with confidence , the eval frameworks, system prompt pipelines, and regression-detection systems that every model launch depends on.

When a new Claude model is ready to ship, this team is the one answering “is it actually better in our products?” When a product team wants to change how Claude behaves, this team owns the tooling that tells them whether they broke something. It’s a platform team whose platform is model behavior itself.

The team sits deliberately at the seam between product engineering and research. You’ll partner closely with other evals groups across the company on shared infrastructure and methodology, with product teams who are shipping features on top of Claude, and with the TPMs and research PMs driving model launches. The pace is set by the model release cadence, and the team operates as both a platform owner and a hands-on partner during launch periods.

Responsibilities

• Lead and grow a team of prompt engineers and platform software engineers
• Own the product-side eval platform: the frameworks, dashboards, bulk runners, and CI integrations that product teams use to measure Claude’s behavior and catch regressions before they ship
• Own system prompt infrastructure: versioning, deployment, rollback, and review tooling for the prompts that run in production across claude.ai, the API, and agentic surfaces
• Be a steady hand through model launches , these are the team’s highest-stakes operational moments and the EM is the backstop when things get chaotic
• Build durable collaboration with other evals groups across the company; this means real work on ownership boundaries, shared roadmaps, and avoiding tragedy-of-the-commons on shared eval infrastructure
• Recruit, close, and retain engineers who want to work at the intersection of product engineering and model behavior
• Shape where the team invests next: there are credible paths into frontier eval development, model launch automation, and deeper prompt engineering support, and part of the job is sequencing them
• Push the team toward measuring things that are hard to measure , behavioral drift, prompt quality, harness parity , not just things that are easy

Requirements

• 8+ years in software engineering with 3+ years managing engineering teams, including experience leading a platform, infra, or developer-tooling team where your customers were other engineers
• A track record of building “pits of success” , tooling and process that made it easy for other teams to do the right thing without needing to understand all the details
• Comfort managing a team with a mixed charter: platform ownership, service-to-other-teams, and a launch-driven operational rhythm, all at once
• Enough technical depth to engage on system design, review pipeline architecture, and be credible in debates with strong ICs , you don’t need to be writing code by hand every day, but you should be able to read it, review it, and be comfortable leveraging Claude to understand, design, and occasionally build.
• A product mindset and willingness to wear multiple hats when the work calls for it
• Demonstrated ability to build and maintain peer relationships with partner orgs that have different cultures and incentives , negotiating ownership, aligning roadmaps, and holding ground when it matters without being territorial about it
• Experience recruiting and closing senior ICs in a competitive market

Nice to Have

• Prior exposure to LLM evals, ML experimentation platforms, or model quality work , even tangentially
• Experience with A/B testing infrastructure, feature flagging, or gradual rollout systems
• Background in devtools, CI/CD platforms, or testing infrastructure at scale
• A history of managing teams that sit between two larger orgs and making that position an asset rather than a liability
• Interest in AI safety and alignment , not required, but it makes the “why” of the work land harder

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.

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