Engineering Manager, Artifacts

Engineering Manager · Manager · Full Time

San FranciscoUSD 347k – 405k1w ago
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Role

What you'll do.

Lead and grow the engineering team building OpenAI's AI-native artifact creation platform spanning documents, spreadsheets, slides, dashboards, and emerging work products. This Engineering Manager role combines hands-on technical leadership with team building, requiring expertise in full-stack systems, model integration, and cross-functional collaboration between research, product, and infrastructure teams.

Responsibilities

  • Team Leadership and Growth: Lead, manage, and develop a team of full-stack and infrastructure-oriented engineers building AI-native artifact creation experiences. Drive hiring strategy, set individual growth plans, conduct performance reviews, and foster a high-performing engineering culture. Scale the team as the product expands across new artifact types and capabilities.
  • Technical Direction and Architecture: Establish technical direction and design architecture across full-stack product systems, generation orchestration, editing and rendering surfaces, storage solutions, reliability infrastructure, and model integration. Make critical architectural decisions balancing near-term velocity with long-term platform extensibility and maintainability.
  • Hands-On Engineering: Remain actively involved in code review, system design, debugging complex failures, and critical product decisions. Contribute directly to high-impact architectural work and participate in on-call responsibilities for production issues. Unblock the team by solving hard technical problems across model behavior, product surfaces, and infrastructure.
  • Research and Model Collaboration: Partner closely with research teams to translate model capabilities, training needs, evaluations, and behavioral insights into shipped product improvements. Communicate bidirectionally between research and product teams, identifying technical requirements for model training and evaluation loops specific to artifact generation.
  • Cross-Functional Product Definition: Collaborate with product, design, infrastructure, and safety teams to define exceptional user experiences for AI-assisted artifact creation. Shape product requirements, contribute to user experience decisions, and ensure engineering perspectives inform product prioritization and feature design.
  • Planning and Execution Strategy: Create comprehensive engineering plans for the next phase of team evolution, including hiring roadmap, execution milestones, technical investments, infrastructure improvements, and operating cadence. Balance competing priorities between near-term product velocity and long-term platform quality, reliability, extensibility, and developer productivity.
  • Complex Problem Debugging and Reliability: Investigate and resolve complex, multi-system failures spanning model behavior, product surfaces, infrastructure bottlenecks, latency issues, and user-facing quality problems. Establish reliability standards, develop evaluation frameworks, and implement monitoring for artifact generation quality and system performance.
  • Category Expansion and Innovation: Help expand the Artifacts team's scope from familiar artifact types (documents, slides, spreadsheets) into new forms of AI-native work products. Explore emerging opportunities for interactive and specialized artifact formats that leverage AI-native capabilities unavailable in traditional tools.

Qualifications

What we look for.

Technical

  • Full-Stack Product Engineering Mastery

    Demonstrated expertise across frontend, backend, infrastructure, and model-facing systems. Ability to reason about distributed systems, database design, API architecture, and cloud infrastructure. Strong understanding of how product layers interact with ML systems and generation pipelines.

  • ML/AI Integration Experience

    Experience building products that integrate or interface with machine learning models, LLMs, or generative AI systems. Understanding of model deployment, serving, inference optimization, latency considerations, and evaluation methodologies for AI-generated outputs.

  • System Design and Architecture

    Proven ability to design scalable, reliable systems handling complex state management, real-time collaboration, data persistence, and model orchestration. Experience making architectural tradeoffs between different implementation approaches and evaluating long-term technical debt.

  • Production Systems Reliability

    Track record building and operating production systems at scale. Experience with monitoring, observability, incident response, performance optimization, and debugging complex production issues across distributed systems and model inference.

Education

  • Computer Science or Related Field

    Bachelor's degree in Computer Science, Software Engineering, Mathematics, Physics, or equivalent practical experience. Strong foundational knowledge in algorithms, data structures, systems design, and computer architecture.

Experience

  • Engineering Leadership

    5+ years of experience leading and mentoring engineering teams, with demonstrated success growing team members into senior roles. Experience setting technical vision, hiring engineers, conducting code reviews, and fostering team culture. Proven ability to balance individual technical contributions with leadership responsibilities.

  • Cross-Functional Collaboration

    Extensive experience working effectively with research, machine learning, product, design, and infrastructure teams. Ability to translate between technical and non-technical stakeholders, communicate complex technical decisions, and drive alignment across diverse functional groups with different priorities.

  • Ambiguous Problem-Solving

    Experience operating successfully in fast-moving, high-ambiguity environments where product strategy, technical architecture, and market landscape are evolving simultaneously. Comfort with iterative discovery, rapid prototyping, and adapting plans based on learning.

  • Consumer or B2B Product Engineering

    Background shipping production products to significant user bases with focus on user experience quality, performance, and reliability. Experience optimizing for metrics like latency, correctness, user satisfaction, and operational efficiency in production systems.

Skills

Required

  • Team Leadership

    Direct experience managing and growing engineering teams. Ability to hire, develop, and retain top technical talent while maintaining high performance standards and fostering psychological safety.

  • Technical Depth Across Stacks

    Strong fundamentals in frontend development, backend systems, database design, and infrastructure. Ability to understand and contribute to code across different technology domains and make informed architectural decisions.

  • System Design and Architecture

    Expertise designing complex distributed systems, evaluating architectural tradeoffs, and making decisions that balance performance, reliability, maintainability, and cost.

  • Strategic Planning

    Ability to translate business goals into engineering roadmaps, prioritize technical investments, identify critical bottlenecks, and create realistic plans with milestone-based execution.

  • Communication and Collaboration

    Exceptional ability to communicate complex technical concepts to diverse audiences, facilitate cross-functional alignment, and drive consensus among teams with competing priorities.

  • Problem-Solving and Debugging

    Strong investigative skills for diagnosing complex issues across multiple systems. Ability to break down ambiguous problems, formulate hypotheses, and systematically identify root causes.

  • AI/ML Product Understanding

    Working knowledge of how generative AI models work, including inference, tokenization, prompt engineering, and evaluation methods. Ability to discuss model capabilities, limitations, and integration patterns with ML researchers and product teams.

Preferred

  • Generative AI / LLM Product Experience

    Nice to have

    Prior experience building products leveraging large language models, generative AI, or similar transformer-based systems. Familiarity with prompt engineering, fine-tuning, evaluation frameworks, or deployment patterns for generative models.

  • Content Collaboration Platform Experience

    Nice to have

    Background working on collaborative editing platforms, document management systems, spreadsheets, slide decks, or similar productivity tools. Understanding of real-time collaboration challenges, conflict resolution, and multi-user editing architectures.

  • Infrastructure and Ops Experience

    Nice to have

    Hands-on experience with cloud infrastructure (AWS, GCP, Azure), containerization, deployment pipelines, or infrastructure-as-code. Understanding of cost optimization, scalability patterns, and operational excellence principles.

  • Research Collaboration

    Nice to have

    Track record collaborating closely with research scientists or ML researchers, translating research findings into product features, or influencing research direction based on product insights and user needs.

  • Evaluation and Analytics

    Nice to have

    Experience designing evaluation frameworks, defining quality metrics, building analytics systems, or working with data to assess product performance and user behavior at scale.

  • Consumer-Scale Product

    Nice to have

    Experience shipping products to millions of users with focus on performance optimization, quality assurance, and maintaining system reliability under scale. Familiarity with monitoring and observability at production scale.

Tech stack

Languages

PythonTypeScript/JavaScriptSQLJava or Go

Frameworks

React or Vue.jsFastAPI or DjangoLangChain or LlamaIndexGraphQL or REST

Databases

PostgreSQLRedisVector Databases (Pinecone, Weaviate, Milvus)NoSQL/Document Stores (MongoDB, DynamoDB)

Tools

Git and GitHubKubernetes and DockerCI/CD Platforms (GitHub Actions, Jenkins, CircleCI)Monitoring and Observability (Datadog, New Relic, Prometheus)Analytics Platforms

Other

LLM APIs and InferenceDistributed Systems PatternsReal-Time Collaboration ArchitectureModel Evaluation Frameworks

Compensation

Pay and benefits.

Base·USD 347,000 – 405,000

Equity·Stock options

Benefits

  • Competitive Equity and Stock Options

    Opportunity for significant equity ownership with meaningful upside participation in OpenAI's growth and success. Options vest over four years with industry-standard terms.

  • Comprehensive Health and Wellness

    Medical, dental, and vision insurance covering employees and dependents. Wellness programs, mental health support, gym stipends, and flexible spending accounts.

  • Professional Development

    Learning budget, conference attendance, technical training, and mentorship opportunities. Access to research papers, educational resources, and collaboration with world-leading AI researchers.

  • Flexible Work Arrangements

    Remote-work flexibility for eligible roles with the ability to collaborate effectively across distributed teams. Balance between focused individual work and collaborative team engagement.

  • Paid Time Off and Leave

    Generous vacation policy, sick leave, parental leave, and sabbatical opportunities. Support for work-life balance and personal priorities.

  • Commuter and Relocation Support

    Pre-tax commuter benefits, parking options, and relocation assistance for candidates joining from outside the San Francisco Bay Area.

  • 401(k) Retirement Plan

    Tax-advantaged retirement savings with employer matching, helping you build long-term financial security.

  • Life and Disability Insurance

    Comprehensive coverage including life insurance, short-term and long-term disability, and supplemental coverage options.

  • Mission-Driven Work

    Opportunity to directly impact AI safety, advancement, and beneficial deployment. Work on products used by millions globally with meaningful contribution to OpenAI's mission of ensuring AI benefits humanity.

Full posting

Original listing.

About the Team

The Artifacts team is building the AI-native creation layer for documents, spreadsheets, slide decks, dashboards, reports, analyses, and new forms of interactive work products. We are rethinking what creation looks like when models can move from an ambiguous user goal to a polished, editable artifact with strong structure, taste, correctness, and speed.

This is a high-agency team working across product, infrastructure, and research. We partner closely with model training teams to shape how frontier models create artifacts, and with ChatGPT product teams to turn those capabilities into experiences that millions of people can use. The work spans full-stack product engineering, model integration, rendering and editing systems, collaboration, storage, evaluation loops, and production reliability.

Our ambition is to build the premier product experience for AI-generated artifacts: starting with familiar work products like slides, sheets, and docs, then expanding into new artifact types that are only possible in an AI-native world.

About the Role

As Engineering Manager, Artifacts, you will lead and grow the engineering team responsible for building this product and technical foundation. You will manage a team of full-stack and infrastructure-oriented engineers, set technical direction, and stay hands-on enough to shape architecture and debug hard problems.

This role sits at the intersection of product engineering, research, and infrastructure. You will partner with researchers on how models are trained and evaluated for artifact creation, with product and design on the user experience.

This is a strong fit for a technical manager who wants to build and ship, not only coordinate. The team has a fast trajectory, so you will help define both the product surface and the team that builds it.

In this role, you will:

  • Lead, manage, and grow a team building AI-native artifact creation experiences across documents, spreadsheets, slide decks, and emerging artifact formats.

  • Set technical direction across full-stack product systems, generation orchestration, editing and rendering surfaces, storage, reliability, and model integration.

  • Responsible for hands-on architecture, code review, debugging, system design, and critical product decisions.

  • Partner closely with research teams to translate model capabilities, training needs, evals, and behavioral insights into shipped product improvements.

  • Work with product, design, infrastructure, and safety partners to define what excellent artifact creation should feel like for users.

  • Create the engineering plan for the next phase of the team, including hiring, execution milestones, technical investments, and operating cadence.

  • Balance near-term product velocity with long-term platform quality, reliability, extensibility, and developer productivity.

  • Debug complex failures across model behavior, product surfaces, infrastructure, latency, and user-facing quality.

  • Help expand the team’s scope from familiar artifact types into new forms of AI-native work products.

You might thrive in this role if you:

  • Have experience leading engineering teams while remaining technically close to the work.

  • Have strong full-stack product engineering fundamentals and can reason across frontend, backend, infrastructure, and model-facing systems.

  • Are excited by AI-native creation tools and have opinions about what makes documents, slides, spreadsheets, dashboards, and interactive artifacts genuinely useful.

  • Can operate in ambiguous, fast-moving environments where the product, model capability, and technical architecture are all evolving at once.

  • Have experience partnering with research, ML, product, design, infrastructure, or data teams.

  • Care about craft, quality, latency, reliability, and user experience, not just whether a system technically works.

  • Have strong judgment about when to build product-specific systems versus reusable platform foundations.

  • Learn quickly, communicate clearly, and bring enough technical depth to raise the bar for the team.

  • Desire to help define and own a new category of AI-native work.

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. 

We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.

For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.

Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.

To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.

We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.

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