Principal Software Engineer, Enterprise Technology Vertical

Principal Engineer · Principal · Full Time

San FranciscoUSD 441k – 500k1w ago
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Role

What you'll do.

Principal Software Engineer at OpenAI's Enterprise Verticals team, leading the design and delivery of AI-powered enterprise workflows for technology companies. This individual-contributor role combines hands-on full-stack engineering with strategic technical leadership, requiring 10+ years of production software development experience and proven expertise in architecting complex distributed systems, shipping applied AI products, and driving adoption at scale across enterprise customers.

Responsibilities

  • Set Technical Direction for Enterprise AI Experiences: Define and drive the technical strategy for role-specific ChatGPT Work experiences across the Technology vertical. Personally architect, design, build, and ship critical components spanning ChatGPT Work surfaces, backend services, connectors, and plugins while establishing patterns and standards that enable other engineers to contribute effectively to the platform.
  • Translate Customer Needs into Product Strategy: Convert ambiguous customer and design-partner requirements into clear, generalizable product and technical strategies with explicit milestones, architectural decisions, and measurable quality and adoption goals. Conduct discovery with enterprise customers and stakeholders to ensure technical decisions drive measurable business outcomes and customer value.
  • Lead Cross-Functional Complex Initiatives: Drive end-to-end coordination across Design, Research, GTM, Security, and platform teams. Align senior stakeholders, make consequential technical and product tradeoffs, resolve competing priorities, and drive decisions through to successful implementation without relying on formal authority.
  • Architect Production-Grade AI Systems: Design and implement sophisticated systems that safely operate probabilistic AI experiences at scale. Establish comprehensive evaluation, instrumentation, security, reliability, staged-rollout, and rollback standards. Define fallback strategies and durable technical contracts across connectors, identity, permissions, enterprise data, and model routing.
  • Own Complete Product and Engineering Lifecycle: Take full ownership from problem definition through sustained iteration. Lead technical design, hands-on prototyping, production implementation, launch strategy, customer feedback loops, and post-launch iteration. Measure success through adoption metrics, customer satisfaction, and reliability indicators in production environments.
  • Establish Engineering Excellence and Mentorship: Raise the technical bar across the team through architecture reviews, reusable patterns, and mentorship of experienced engineers. Build durable technical foundations, document critical architectural decisions, and create knowledge artifacts that enable team scaling while maintaining quality and security standards.
  • Operationalize Enterprise-Grade Reliability: Implement comprehensive observability, monitoring, and incident response capabilities for mission-critical workflows. Ensure proper handling of partial failures, data consistency guarantees, and secure data flows. Manage staged rollouts, canary deployments, and rollback procedures to minimize production risk and customer impact.

Qualifications

What we look for.

Technical

  • Full-Stack Production System Architecture

    Demonstrated expertise designing and implementing sophisticated systems across frontend, backend, APIs, data layers, and distributed services. Proven ability to make foundational architectural tradeoffs, understand performance implications, and scale systems to handle enterprise workloads with millions of operations.

  • Applied AI and LLM Systems Development

    Hands-on experience shipping applied AI, agentic, or conversational products in production environments. Practical understanding of model behavior, tool use, grounding in external data, evaluation frameworks, human feedback integration, and the unique reliability challenges of probabilistic systems versus deterministic software.

  • Enterprise Identity and Security Architecture

    Deep expertise in enterprise identity systems, authorization frameworks, secure data flows, and compliance requirements. Experience designing systems that handle sensitive data, enforce permissions at scale, maintain auditability, and meet enterprise security standards for regulated industries.

  • Distributed Systems and Resilience Patterns

    Expert-level understanding of distributed systems, API design, data models, partial-failure behavior, circuit breakers, retry logic, idempotency, and eventual consistency patterns. Proven track record designing systems that remain reliable under adversarial conditions and component failures.

  • Production Operations and Observability

    Extensive experience with production monitoring, comprehensive logging and tracing, error tracking, performance profiling, and incident response procedures. Ability to instrument systems for visibility, set up alerting strategies, conduct post-mortems, and iteratively improve system reliability based on production telemetry.

Education

  • Computer Science or Related Field Degree

    Bachelor's degree in Computer Science, Computer Engineering, Software Engineering, or equivalent practical engineering experience demonstrating mastery of core computer science fundamentals including algorithms, data structures, systems design, and software architecture principles.

Experience

  • 10+ Years Building Production Software

    Minimum ten years of hands-on experience building, shipping, and operating production software systems. This experience should demonstrate progression from building individual features to owning complete product surfaces and systems, with proven ability to navigate technical complexity and drive adoption at scale.

  • Complex Integration-Heavy Systems Leadership

    Proven track record leading the architecture and hands-on delivery of integration-heavy or distributed systems serving multiple enterprise customers or use cases. Demonstrated ability to reduce ambiguity, establish clear technical direction, and execute over extended timeframes while maintaining quality and reliability.

  • Business-Critical System Ownership

    Direct ownership and operational responsibility for business-critical production systems at scale, including architecture decisions, performance optimization, reliability improvements, comprehensive testing strategies, incident response leadership, data migrations, and ongoing operational excellence. Experience managing systems with high availability and uptime requirements.

  • Product-Minded Engineering Leadership

    Track record of connecting technical decisions directly to measurable customer outcomes, adoption metrics, and business success. Demonstrated ability to influence product direction, work directly with customers and stakeholders, and maintain technical rigor while pragmatically solving real customer problems.

Skills

Required

  • React and TypeScript

    Production-level expertise building modern frontend applications with React and TypeScript. Strong understanding of component architecture, state management, performance optimization, and building performant user interfaces at scale for enterprise applications.

  • Backend Languages (Python, Go, or Node.js)

    Expert-level proficiency in at least one backend language, with production experience in Python, Go, Node.js, or comparable systems languages. Demonstrated ability to design efficient APIs, handle concurrent workloads, and build performant backend services.

  • API Design and Integration

    Expert understanding of RESTful and modern API design patterns, webhook integration, third-party service integrations, authentication protocols (OAuth 2.0, SAML), and rate limiting strategies. Proven ability to design APIs that scale with enterprise customer needs.

  • Data Systems and Modeling

    Strong expertise in relational and document database design, data modeling for complex workflows, query optimization, and understanding tradeoffs between consistency, availability, and partition tolerance. Experience with data pipelines, ETL patterns, and analytics infrastructure.

  • System Design and Architecture

    Expert-level ability to design scalable, reliable systems from first principles. Capability to evaluate architectural options, make informed tradeoffs regarding technology choices, and establish patterns that scale with organizational growth.

  • Security and Compliance

    Deep understanding of authentication, authorization, encryption, secure data handling, and compliance requirements. Experience building systems that handle sensitive data, maintain audit trails, and meet enterprise security standards.

  • Observability and Production Operations

    Advanced expertise in structured logging, distributed tracing, metrics collection, alerting strategies, and incident response. Ability to design systems that provide visibility into production behavior and enable quick problem identification and resolution.

Preferred

  • LLM Application Development

    Nice to have

    Hands-on experience building production applications leveraging large language models, including prompt engineering, fine-tuning strategies, retrieval-augmented generation (RAG), prompt chaining, and managing LLM API integrations at scale.

  • Workflow Automation and Orchestration

    Nice to have

    Experience designing workflow engines, automation platforms, or orchestration systems that coordinate complex multi-step processes. Understanding of state management, error handling, and scheduling in workflow systems serving diverse use cases.

  • Analytics and Visualization Platforms

    Nice to have

    Background building analytics platforms, dashboards, or visualization systems that enable non-technical users to extract insights from complex data. Experience designing intuitive interfaces for data exploration and actionable insights.

  • Enterprise SaaS Architecture

    Nice to have

    Track record building SaaS products serving enterprise customers, including experience with multi-tenancy, resource isolation, usage metering, billing integration, and scaling to handle diverse customer requirements and workload patterns.

  • Staged Rollout and Canary Deployment

    Nice to have

    Practical experience implementing sophisticated deployment strategies including canary releases, blue-green deployments, feature flags, and progressive rollouts. Understanding of monitoring strategies to catch issues in early deployment phases.

  • Agentic and Tool-Use Systems

    Nice to have

    Experience building systems where AI agents independently make decisions about tool selection and execution. Understanding of grounding techniques, verification strategies, and ensuring reliable behavior when systems have agency over workflows.

Tech stack

Languages

PythonTypeScriptGoNode.jsSQL

Frameworks

ReactNext.jsFastAPIExpress.js or SimilarGraphQLgRPC

Databases

PostgreSQLMongoDB or Document DatabasesRedisElasticsearchBigQuery or Data Warehousing

Tools

Git and GitHubDocker and KubernetesCI/CD Pipelines (GitHub Actions, GitLab CI)Monitoring and Observability (Datadog, New Relic, Grafana)API Testing and Documentation (Postman, OpenAPI)Project Management (Linear, Jira)

Other

Enterprise Identity Systems (OAuth 2.0, SAML, OIDC)Message Queues (Kafka, RabbitMQ, Pub/Sub)Testing Frameworks (Jest, pytest, Go testing)Infrastructure as Code (Terraform)Machine Learning Frameworks (PyTorch, TensorFlow)LLM APIs and Orchestration (OpenAI API, LangChain)

Compensation

Pay and benefits.

Base·USD 441,000 – 500,000

Equity·Stock options

Benefits

  • Comprehensive Health and Wellness Coverage

    Medical, dental, and vision insurance with competitive coverage levels. Mental health support and wellness programs designed to support employee wellbeing and work-life balance.

  • Retirement Planning and Financial Security

    401(k) retirement plan with employer matching contributions, helping you build long-term financial security and retirement savings.

  • Equity Participation

    Stock options or equity grants enabling employees to participate in OpenAI's growth and success. Valuable for long-term wealth building at a high-growth AI organization.

  • Flexible Time Off

    Generous paid time off (PTO) policy including vacation days, sick leave, and personal time. Support for work-life balance and personal commitments throughout the year.

  • Professional Development and Learning

    Investment in professional growth through conference attendance, training programs, and technical certifications. Support for continuous learning and skill development in evolving technology landscape.

  • Competitive Base Salary and Performance Bonuses

    Competitive compensation packages with performance-based bonus structures. Rewards for exceptional contributions and achievement of business objectives.

  • Remote Work Flexibility

    Flexible work arrangements supporting remote or hybrid work options. Flexibility to work from home or other locations while collaborating effectively with distributed teams.

  • Commuter Benefits and Transportation

    Commuter benefits, transit passes, and parking support where applicable. Support for convenient and sustainable commuting options to offices.

  • Parental Leave and Family Benefits

    Comprehensive parental leave policies for new parents. Support for growing families and work-life integration around major life events.

  • Charitable Giving and Volunteer Time

    Matching gift programs and paid volunteer time off. Opportunity to support causes you care about and give back to the community.

Full posting

Original listing.

About the Team

Enterprise Verticals builds role-specific ChatGPT Work experiences for high-value enterprise workflows. We combine product engineering, plugins and skills, connectors, data, evaluations, and customer evidence to turn useful demos into reliable daily work.

This opening sits within the Technology vertical inside Enterprise Verticals. The group focuses on repeatable workflows for people at technology companies, beginning with functions such as data and analytics, sales, and design, and carries the shared platform needs—tool integration, permissions, quality measurement, and safe rollout—across those experiences.

We work closely with Design, Research, GTM, Security, and platform teams, as well as with customers and design partners. Success means that people can reach a trustworthy first result, understand what the system did, and keep using the workflow—not merely that a prototype exists.

About the Role

We are looking for an exceptionally experienced, hands-on full-stack engineer to define and build the next generation of AI-powered enterprise workflows. You will take on the hardest and most ambiguous problems in the Technology vertical: translating real customer needs into product direction, designing the systems behind the experience, and personally writing and shipping production-quality code across the stack.

You will own the technical direction and end-to-end delivery of products spanning ChatGPT Work surfaces, backend services, plugins, connectors, enterprise data, permissions, and evaluations. You will make foundational architecture and product tradeoffs; establish patterns other engineers can build on; and hold these experiences to a high bar for reliability, security, observability, and customer value.

This is an individual-contributor role for an engineer who leads through technical judgment, direct execution, and influence—not people management. You should be equally comfortable working directly with customers, setting direction with senior cross-functional and platform partners, debugging complex production behavior, and staying close to the code. Success means taking a meaningful enterprise product from first principles through adoption at scale.


Responsibilities:

  • Set the technical direction for role-specific enterprise AI experiences, and personally design, build, and ship their most critical components across ChatGPT Work surfaces, services, plugins, and connectors.

  • Turn ambiguous customer and design-partner needs into a clear, generalizable product and technical strategy, with explicit milestones, architectural decisions, and measurable quality and adoption goals.

  • Lead complex initiatives across Design, Research, GTM, Security, and platform teams; align senior stakeholders; make consequential tradeoffs; and drive decisions through to implementation.

  • Architect production-grade systems and establish the evaluation, instrumentation, security, reliability, staged-rollout, and rollback standards required to operate probabilistic AI experiences safely.

  • Own the complete product and engineering lifecycle: problem definition, technical design, hands-on prototyping, production implementation, launch, customer feedback, and sustained iteration.

  • Define durable technical contracts and fallback strategies across connectors, identity, permissions, enterprise data, model routing, and shared platform dependencies; raise the engineering bar through architecture reviews, mentorship, and reusable patterns.

You might thrive in this role if:

  • You are a deeply experienced, hands-on product engineer—typically with 10+ years building production software—who combines exceptional technical depth with strong product judgment.

  • You can independently architect and implement sophisticated systems across frontend, backend, APIs, data, distributed services, and complex enterprise integrations.

  • You can earn trust with customers, influence senior stakeholders, and bring cross-functional teams to a clear decision without relying on formal authority.

  • You know how to turn uncertainty into a disciplined execution plan, using experiments, evaluations, instrumentation, and customer evidence to decide what to build.

  • You treat enterprise identity, permissions, privacy, security, performance, reliability, and operational readiness as foundational product requirements.

  • You have repeatedly led the architecture and hands-on delivery of important user-facing products from ambiguous beginnings through production use, and can explain the technical and product decisions that made them succeed.

  • You know when to build quickly, when to invest in foundational systems, and how to turn a specific customer workflow into a durable product that serves many customers.

Preferred qualifications

  • Extensive experience personally building and operating full-stack production products, including modern frontend technologies such as React and TypeScript and backend services in Python, Go, Node.js, or comparable languages.

  • A track record of setting technical direction for complex, integration-heavy or distributed systems, with deep understanding of APIs, data models, enterprise identity, authorization, secure data flows, and partial-failure behavior.

  • Demonstrated ownership of business-critical production systems at scale, including architecture, performance, observability, testing, incident response, migrations, staged delivery, and operational excellence.

  • Experience shipping applied AI, agentic, or conversational products, with a practical understanding of model behavior, tool use, grounding, evaluations, human feedback, and the reliability challenges of probabilistic systems.

  • Experience designing and building sophisticated workflow, data, analytics, visualization, or insight products that make complex systems genuinely useful to enterprise users.

  • A strong record of leading through technical judgment, mentoring experienced engineers, shaping cross-team architecture, and connecting engineering decisions to measurable customer outcomes and sustained adoption.

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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