This role sits at the intersection of product thinking and full-stack engineering. You'll work directly with researchers and engineers to deeply understand their workflows, identify bottlenecks, and rapidly ship solutions that multiply their productivity. Whether you're building human feedback interfaces for model evaluation, creating platforms for experiment orchestration, or developing novel visualization tools for understanding model behavior, your work will directly accelerate our mission to build safe, reliable AI systems.

We're looking for someone who can operate with high agency in an ambiguous environment,someone who can be dropped into a research team, quickly develop domain expertise, and independently drive impactful projects from conception to delivery.

Responsibilities:

• Build and maintain full-stack applications and infrastructure that researchers use daily to conduct experiments, collect feedback, and analyze results
• Partner closely with research teams to understand their workflows, pain points, and requirements, translating these into technical solutions
• Design intuitive interfaces and abstractions that make complex research tasks accessible and efficient
• Create reusable platforms and tools that accelerate the development of new research applications
• Rapidly prototype and iterate on solutions, gathering feedback from users and refining based on real-world usage
• Take ownership of complete product areas, from understanding user needs through design, implementation, and ongoing iteration
• Contribute to technical strategy and architectural decisions for research tooling
• Mentor other engineers and help establish best practices for research application development

Requirements:

• 5+ years of software engineering experience with a strong focus on full-stack development
• Excel at rapid iteration and shipping,you can move from concept to working prototype quickly
• Have experience building tools, platforms, or infrastructure for technical users (engineers, researchers, data scientists, analysts, etc.)
• Demonstrate high agency and ability to operate independently in ambiguous environments
• Can quickly develop deep understanding of complex technical domains
• Have strong product instincts and can identify the right problems to solve
• Are proficient with modern web technologies (React, TypeScript, Python, etc.)
• Have a track record of building user-facing applications that are actually used and loved by their target audience
• Communicate effectively with both technical and non-technical stakeholders
• Care about the societal impacts of your work and are motivated by Anthropic's mission

Strong candidates may also have:

• Experience building research tools, scientific software, or experimentation platforms
• Background in machine learning, AI research, or working closely with ML researchers
• Founded or been an early engineer at a startup, particularly one focused on developer or researcher tools
• Built open-source tools or platforms with active user communities
• Experience with data visualization, interactive interfaces, or novel interaction paradigms
• Contributed to engineering platforms or internal tooling at scale (similar to Heroku, Vercel, or other platform-as-a-service products)
• Experience leveraging AI/LLMs to build more powerful or efficient tools
• Previous work in creative tools, artist tools, or other domains requiring deep user empathy
• Domain knowledge in areas like human-computer interaction, systems safety, or AI alignment

Annual compensation range for this role is $300,000-$405,000 USD.

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Location

New York City

Employment Type

Full time

Location Type

Hybrid

Department

Model Deployment for Business

Compensation

• $198K – $335K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

Benefits

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

About the team

OpenAI’s Forward Deployed Engineering team partners with global pharma and biotech, CROs, and research institutions to deploy existing expertise across the R&D value chain to help customers design and ship production-grade AI systems. We operate at the intersection of customer delivery and core platform development, converting early deployments into repeatable system standards and evaluation practices that scale across regulated environments.

About the role

We are hiring a Forward Deployed Engineer (FDE) to push the frontier on what is possible today across drug discovery (e.g., target identification, molecular design, pre-clinical) and development (e.g., trial design, trial ops, biostats) by leading end-to-end deployments of our models inside life sciences organizations and research institutions. You will work with customers who are deep experts in their scientific or operational domains, translating real-world data, infrastructure, and constraints into production systems.

You will measure success through production adoption, measurable workflow impact, and eval-driven feedback loops, including evaluation benchmarks and acceptance criteria, that inform product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM to deliver in regulated contexts, including inspection readiness with audit trails and traceable evidence.

This role is based in NYC. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required.

In this role you will

• Design and ship production systems around models, owning integrations, data provenance, reliability, and on-call readiness across research, clinical, and operational workflows.

• Lead discovery and scoping from pre-sales through post-sales, translating ambiguous workflow needs into hypothesis-driven problem framing, system requirements, and an execution plan with measurable endpoints.

• Define and enforce launch criteria for regulated contexts, including validation evidence, audit readiness, outcome metrics, and drive delivery until we demonstrate sustained production impact.

• Build in sensitive scientific data environments where auditability, validation, and access controls shape architecture, operating procedures, and failure handling.

• Run evaluation loops that measure model and system quality against workflow-specific scientific benchmarks and use results to drive model and product changes.

• Distill deployment learnings into hardened primitives, reference architectures, validation templates, and benchmark harnesses that scale across regulated life sciences environments.

You might thrive in this role if you

• Bring 5+ years of software/ML engineering or technical deployment experience with customer-facing ownership in biotech, pharma, clinical research, or scientific software; PhD, MS, or equivalent applied experience in a life sciences relevant field encouraged.

• Have owned customer GenAI deployments end-to-end from scoping through production adoption, and improved them through evaluation design, error analysis, and iterative evidence generation that tightens acceptance criteria over time.

• Have delivered AI systems in trial design, regulatory writing, or scientific operations where validation strategy, auditability, compliance constraints, and reviewer expectations shaped system design and rollout.

• Communicate clearly across scientific, clinical, model research, technical, and executive audiences, translating technical tradeoffs into decision quality, risk posture, and measurable outcomes with credibility.

• Apply systems thinking with high execution standards, consistently turning failures, escalations, and audit findings into improved operating standards, validation artifacts, and process improvements.

What we offer

• Competitive salary and equity package

• Opportunity to work with a talented team of engineers and researchers

• Collaborative and dynamic work environment

• Professional development and growth opportunities

• Flexible work arrangements

• Comprehensive benefits package

• Access to cutting-edge technology and resources

How to apply

If you are a motivated and talented individual who is passionate about AI and life sciences, we encourage you to apply for this exciting opportunity. Please submit your resume and a cover letter explaining why you are a strong fit for this role.

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Location

San Francisco

Employment Type

Full time

Location Type

Hybrid

Department

Model Deployment for Business

Compensation

• $198K – $335K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

Benefits

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

About the team

OpenAI’s Forward Deployed Engineering team partners with global pharma and biotech, CROs, and research institutions to deploy existing expertise across the R&D value chain to help customers design and ship production-grade AI systems. We operate at the intersection of customer delivery and core platform development, converting early deployments into repeatable system standards and evaluation practices that scale across regulated environments.

About the role

We are hiring a Forward Deployed Engineer (FDE) to push the frontier on what is possible today across drug discovery (e.g., target identification, molecular design, pre-clinical) and development (e.g., trial design, trial ops, biostats) by leading end-to-end deployments of our models inside life sciences organizations and research institutions. You will work with customers who are deep experts in their scientific or operational domains, translating real-world data, infrastructure, and constraints into production systems.

Responsibilities

• Design and ship production systems around models, owning integrations, data provenance, reliability, and on-call readiness across research, clinical, and operational workflows.

• Lead discovery and scoping from pre-sales through post-sales, translating ambiguous workflow needs into hypothesis-driven problem framing, system requirements, and an execution plan with measurable endpoints.

• Define and enforce launch criteria for regulated contexts, including validation evidence, audit readiness, outcome metrics, and drive delivery until we demonstrate sustained production impact.

• Build in sensitive scientific data environments where auditability, validation, and access controls shape architecture, operating procedures, and failure handling.

• Run evaluation loops that measure model and system quality against workflow-specific scientific benchmarks and use results to drive model and product changes.

• Distill deployment learnings into hardened primitives, reference architectures, validation templates, and benchmark harnesses that scale across regulated life sciences environments.

Requirements

• Bring 5+ years of software/ML engineering or technical deployment experience with customer-facing ownership in biotech, pharma, clinical research, or scientific software; PhD, MS, or equivalent applied experience in a life sciences relevant field encouraged.

• Have owned customer GenAI deployments end-to-end from scoping through production adoption, and improved them through evaluation design, error analysis, and iterative evidence generation that tightens acceptance criteria over time.

• Have delivered AI systems in trial design, regulatory writing, or scientific operations where validation strategy, auditability, compliance constraints, and reviewer expectations shaped system design and rollout.

• Communicate clearly across scientific, clinical, model research, technical, and executive audiences, translating technical tradeoffs into decision quality, risk posture, and measurable outcomes with credibility.

• Apply systems thinking with high execution standards, consistently turning failures, escalations, and audit findings into improved operating standards, validat

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Location

Paris, France

Employment Type

Full time

Location Type

Hybrid

Department

Model Deployment for Business

About the team

OpenAI’s Forward Deployed Engineering team partners with global pharma and biotech, CROs, and research institutions to deploy existing expertise across the R&D value chain to help customers design and ship production-grade AI systems. We operate at the intersection of customer delivery and core platform development, converting early deployments into repeatable system standards and evaluation practices that scale across regulated environments.

About the role

We are hiring a Forward Deployed Engineer (FDE) to push the frontier on what is possible today across drug discovery (e.g., target identification, molecular design, pre-clinical) and development (e.g., trial design, trial ops, biostats) by leading end-to-end deployments of our models inside life sciences organizations and research institutions. You will work with customers who are deep experts in their scientific or operational domains, translating real-world data, infrastructure, and constraints into production systems.

You will measure success through production adoption, measurable workflow impact, and eval-driven feedback loops, including evaluation benchmarks and acceptance criteria, that inform product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM to deliver in regulated contexts, including inspection readiness with audit trails and traceable evidence.

This role is based in Paris. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required.

In this role you will

• Design and ship production systems around models, owning integrations, data provenance, reliability, and on-call readiness across research, clinical, and operational workflows.

• Lead discovery and scoping from pre-sales through post-sales, translating ambiguous workflow needs into hypothesis-driven problem framing, system requirements, and an execution plan with measurable endpoints.

• Define and enforce launch criteria for regulated contexts, including validation evidence, audit readiness, outcome metrics, and drive delivery until we demonstrate sustained production impact.

• Build in sensitive scientific data environments where auditability, validation, and access controls shape architecture, operating procedures, and failure handling.

• Run evaluation loops that measure model and system quality against workflow-specific scientific benchmarks and use results to drive model and product changes.

• Distill deployment learnings into hardened primitives, reference architectures, validation templates, and benchmark harnesses that scale across regulated life sciences environments.

You might thrive in this role if you

• Bring 5+ years of software/ML engineering or technical deployment experience with customer-facing ownership in biotech, pharma, clinical research, or scientific software; PhD, MS, or equivalent applied experience in a life sciences relevant field encouraged.

• Have owned customer GenAI deployments end-to-end from scoping through production adoption, and improved them through evaluation design, error analysis, and iterative evidence generation that tightens acceptance criteria over time.

• Have delivered AI systems in trial design, regulatory writing, or scientific operations where validation strategy, auditability, compliance constraints, and reviewer expectations shaped system design and rollout.

• Communicate clearly across scientific, clinical, model research, technical, and executive audiences, translating technical tradeoffs into decision quality, risk posture, and measurable outcomes with credibility.

• Apply systems thinking with high execution standards, consistently turning failures, escalations, and audit findings into improved operating standards, validation artifacts, and repeatable deployment playbooks.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

XML job scraping automation by YubHub

Location

San Francisco

Employment Type

Full time

Location Type

Hybrid

Department

Model Deployment for Business

Compensation

• $252K – $335K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

About the team

OpenAI’s Forward Deployed Engineering (FDE) team partners with global pharma and biotech, CROs, and research institutions to deploy production-grade AI systems across the R&D value chain. We operate at the intersection of customer delivery and core platform development, converting early deployments into repeatable system standards and evaluation practices that scale across regulated environments.

About the role

As a Life Sciences FDE Manager, you’ll lead a team of FDEs delivering production AI systems across drug discovery and development workflows. You’ll own delivery outcomes and team leverage while staying hands-on as a player-coach. This includes building and shipping alongside the team, setting technical direction, and maintaining a high bar for production-grade systems in regulated environments.

We measure success through the health and quality of your FDE team, production adoption and measurable workflow impact, the quality of eval-driven feedback delivered back to Product and Research, and the repeatability of deployment patterns across life sciences customers.

This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. This role will require travel up to 25%.

In this role you will

• Lead and grow a team of FDEs delivering production AI systems across regulated life sciences environments

• Be accountable for your team’s end-to-end delivery outcomes, balancing scope, speed, robustness, and risk in high-stakes deployments

• Coach and develop engineers through direct feedback, high technical standards, and clear expectations for execution and ownership

• Operate as a player-coach, directly contributing to production systems while leading, coaching, and setting technical direction

• Guide teams through ambiguous, multi-workstream engagements spanning data, workflows, infrastructure, security, and scientific stakeholders

• Run evaluation loops that measure model and system quality against workflow-specific scientific benchmarks, then convert results into crisp roadmap input

You might thrive in this role if you

• Bring 8+ years of engineering or technical delivery experience, including 2+ years managing high-performing customer-facing or systems-oriented engineering teams

• Have led complex, high-pressure technical programs from prototype through sustained production use in regulated environments

• Have experience working in or adjacent to life sciences R&D, clinical research, scientific software, or regulated scientific data environments

• Write and review production-grade code and can guide architectural decisions across backend, data, and ML-adjacent systems

• Translate scientific and technical tradeoffs into clear delivery plans, risk posture, and measurable outcomes across scientific, clinical, technical, and executive audiences

• Elevate team performance through clarity, judgment, and technical credibility

• Turn field experience into precise, actionable feedback for Product, Research, and GTM teams

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

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Location

London, UK

Employment Type

Full time

Location Type

Hybrid

Department

Model Deployment for Business

About the team

OpenAI’s Forward Deployed Engineering team partners with global pharma and biotech, CROs, and research institutions to deploy existing expertise across the R&D value chain to help customers design and ship production-grade AI systems. We operate at the intersection of customer delivery and core platform development, converting early deployments into repeatable system standards and evaluation practices that scale across regulated environments.

About the role

We are hiring a Forward Deployed Engineer (FDE) to push the frontier on what is possible today across drug discovery (e.g., target identification, molecular design, pre-clinical) and development (e.g., trial design, trial ops, biostats) by leading end-to-end deployments of our models inside life sciences organizations and research institutions. You will work with customers who are deep experts in their scientific or operational domains, translating real-world data, infrastructure, and constraints into production systems.

You will measure success through production adoption, measurable workflow impact, and eval-driven feedback loops, including evaluation benchmarks and acceptance criteria, that inform product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM to deliver in regulated contexts, including inspection readiness with audit trails and traceable evidence.

This role is based in London. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required.

In this role you will

• Design and ship production systems around models, owning integrations, data provenance, reliability, and on-call readiness across research, clinical, and operational workflows.

• Lead discovery and scoping from pre-sales through post-sales, translating ambiguous workflow needs into hypothesis-driven problem framing, system requirements, and an execution plan with measurable endpoints.

• Define and enforce launch criteria for regulated contexts, including validation evidence, audit readiness, outcome metrics, and drive delivery until we demonstrate sustained production impact.

• Build in sensitive scientific data environments where auditability, validation, and access controls shape architecture, operating procedures, and failure handling.

• Run evaluation loops that measure model and system quality against workflow-specific scientific benchmarks and use results to drive model and product changes.

• Distill deployment learnings into hardened primitives, reference architectures, validation templates, and benchmark harnesses that scale across regulated life sciences environments.

You might thrive in this role if you

• Bring 5+ years of software/ML engineering or technical deployment experience with customer-facing ownership in biotech, pharma, clinical research, or scientific software; PhD, MS, or equivalent applied experience in a life sciences relevant field encouraged.

• Have owned customer GenAI deployments end-to-end from scoping through production adoption, and improved them through evaluation design, error analysis, and iterative evidence generation that tightens acceptance criteria over time.

• Have delivered AI systems in trial design, regulatory writing, or scientific operations where validation strategy, auditability, compliance constraints, and reviewer expectations shaped system design and rollout.

• Communicate clearly across scientific, clinical, model research, technical, and executive audiences, translating technical tradeoffs into decision quality, risk posture, and measurable outcomes with credibility.

• Apply systems thinking with high execution standards, consistently turning failures, escalations, and audit findings into improved operating standards, validation artifacts, and repeatable deployment playbooks.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

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Location

Dublin, Ireland

Employment Type

Full time

Location Type

Hybrid

Department

Model Deployment for Business

About the team

OpenAI’s Forward Deployed Engineering team partners with global pharma and biotech, CROs, and research institutions to deploy existing expertise across the R&D value chain to help customers design and ship production-grade AI systems. We operate at the intersection of customer delivery and core platform development, converting early deployments into repeatable system standards and evaluation practices that scale across regulated environments.

About the role

We are hiring a Forward Deployed Engineer (FDE) to push the frontier on what is possible today across drug discovery (e.g., target identification, molecular design, pre-clinical) and development (e.g., trial design, trial ops, biostats) by leading end-to-end deployments of our models inside life sciences organizations and research institutions. You will work with customers who are deep experts in their scientific or operational domains, translating real-world data, infrastructure, and constraints into production systems.

You will measure success through production adoption, measurable workflow impact, and eval-driven feedback loops, including evaluation benchmarks and acceptance criteria, that inform product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM to deliver in regulated contexts, including inspection readiness with audit trails and traceable evidence.

This role is based in Dublin. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required.

In this role you will

• Design and ship production systems around models, owning integrations, data provenance, reliability, and on-call readiness across research, clinical, and operational workflows.

• Lead discovery and scoping from pre-sales through post-sales, translating ambiguous workflow needs into hypothesis-driven problem framing, system requirements, and an execution plan with measurable endpoints.

• Define and enforce launch criteria for regulated contexts, including validation evidence, audit readiness, outcome metrics, and drive delivery until we demonstrate sustained production impact.

• Build in sensitive scientific data environments where auditability, validation, and access controls shape architecture, operating procedures, and failure handling.

• Run evaluation loops that measure model and system quality against workflow-specific scientific benchmarks and use results to drive model and product changes.

• Distill deployment learnings into hardened primitives, reference architectures, validation templates, and benchmark harnesses that scale across regulated life sciences environments.

You might thrive in this role if you

• Bring 5+ years of software/ML engineering or technical deployment experience with customer-facing ownership in biotech, pharma, clinical research, or scientific software; PhD, MS, or equivalent applied experience in a life sciences relevant field encouraged.

• Have owned customer GenAI deployments end-to-end from scoping through production adoption, and improved them through evaluation design, error analysis, and iterative evidence generation that tightens acceptance criteria over time.

• Have delivered AI systems in trial design, regulatory writing, or scientific operations where validation strategy, auditability, compliance constraints, and reviewer expectations shaped system design and rollout.

• Communicate clearly across scientific, clinical, model research, technical, and executive audiences, translating technical tradeoffs into decision quality, risk posture, and measurable outcomes with credibility.

• Apply systems thinking with high execution standards, consistently turning failures, escalations, and audit findings into improved operating standards, validation artifacts, and repeatable deployment playbooks.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

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Location

Munich, Germany

Employment Type

Full time

Location Type

Hybrid

Department

Model Deployment for Business

About the team

OpenAI’s Forward Deployed Engineering team partners with global pharma and biotech, CROs, and research institutions to deploy existing expertise across the R&D value chain to help customers design and ship production-grade AI systems. We operate at the intersection of customer delivery and core platform development, converting early deployments into repeatable system standards and evaluation practices that scale across regulated environments.

About the role

We are hiring a Forward Deployed Engineer (FDE) to push the frontier on what is possible today across drug discovery (e.g., target identification, molecular design, pre-clinical) and development (e.g., trial design, trial ops, biostats) by leading end-to-end deployments of our models inside life sciences organizations and research institutions. You will work with customers who are deep experts in their scientific or operational domains, translating real-world data, infrastructure, and constraints into production systems.

You will measure success through production adoption, measurable workflow impact, and eval-driven feedback loops, including evaluation benchmarks and acceptance criteria, that inform product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM to deliver in regulated contexts, including inspection readiness with audit trails and traceable evidence.

This role is based in Munich. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required.

In this role you will

• Design and ship production systems around models, owning integrations, data provenance, reliability, and on-call readiness across research, clinical, and operational workflows.

• Lead discovery and scoping from pre-sales through post-sales, translating ambiguous workflow needs into hypothesis-driven problem framing, system requirements, and an execution plan with measurable endpoints.

• Define and enforce launch criteria for regulated contexts, including validation evidence, audit readiness, outcome metrics, and drive delivery until we demonstrate sustained production impact.

• Build in sensitive scientific data environments where auditability, validation, and access controls shape architecture, operating procedures, and failure handling.

• Run evaluation loops that measure model and system quality against workflow-specific scientific benchmarks and use results to drive model and product changes.

• Distill deployment learnings into hardened primitives, reference architectures, validation templates, and benchmark harnesses that scale across regulated life sciences environments.

You might thrive in this role if you

• Bring 5+ years of software/ML engineering or technical deployment experience with customer-facing ownership in biotech, pharma, clinical research, or scientific software; PhD, MS, or equivalent applied experience in a life sciences relevant field encouraged.

• Have owned customer GenAI deployments end-to-end from scoping through production adoption, and improved them through evaluation design, error analysis, and iterative evidence generation that tightens acceptance criteria over time.

• Have delivered AI systems in trial design, regulatory writing, or scientific operations where validation strategy, auditability, compliance constraints, and reviewer expectations shaped system design and rollout.

• Communicate clearly across scientific, clinical, model research, technical, and executive audiences, translating technical tradeoffs into decision quality, risk posture, and measurable outcomes with credibility.

• Apply systems thinking with high execution standards, consistently turning failures, escalations, and audit findings into improved operating standards, validation artifacts, and repeatable deployment playbooks.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

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