Senior Staff Software Engineer, Engineering Acceleration | Consumer Devices

About the role

This position focuses on building the internal infrastructure and developer platforms that support our consumer hardware and software initiatives. You will design the build, test, and deployment systems that allow our engineers to ship high-quality code across cloud and device environments. The role requires deep collaboration with hardware and software teams to ensure platform decisions serve the needs of diverse product lines. You will own the reliability, scalability, and developer experience of critical infrastructure components used across the organization. The ideal candidate thrives in ambiguous environments and turns strategic goals into executable technical roadmaps. You will mentor other engineers by example, elevating the standard for code quality, system design, and operational excellence. Your work will directly influence the speed and safety with which OpenAI brings AI-powered consumer devices to market.

Key facts

What you'll do

• Architect and maintain CI/CD systems for software running on both hardware devices and cloud platforms, ensuring pipelines are robust, scalable, and observable.
• Create self-service workflows and platform primitives that minimize manual tasks and accelerate the development lifecycle for cross-functional engineering teams.
• Implement security standards within delivery pipelines, including secrets management, access control, and supply chain integrity to protect critical infrastructure and code artifacts.
• Partner with cross-functional teams to identify bottlenecks in the development lifecycle and translate these insights into concrete platform improvements and automation.
• Establish and maintain metrics to measure platform performance, such as build duration, deployment frequency, failure rates, and system reliability, using data to drive iterative enhancements.
• Participate in on-call rotations for the infrastructure managed by the team, providing timely response and leadership during critical incidents and outages.
• Use automation and AI-native tools to optimize debugging, testing processes, and developer workflows, reducing cognitive load and improving overall productivity.
• Evaluate emerging technologies and tools, conducting proof-of-concept projects to assess their viability for integration into the platform at scale.
• Collaborate with security and compliance stakeholders to ensure that platform changes adhere to regulatory requirements and internal governance policies.
• Mentor staff and senior engineers by leading design reviews, code reviews, and architectural discussions that raise the bar for engineering practices.
• Drive standardization across teams by defining best practices for infrastructure as code, versioning strategies, and deployment patterns for heterogeneous environments.
• Act as a technical leader in scoping platform initiatives, making informed trade-offs between speed, maintainability, and long-term operational sustainability.

Requirements

• 10+ years of professional software engineering experience, with a strong track record of delivering complex systems in production environments.
• 5+ years of direct experience in developer productivity, CI/CD, or internal platform engineering, demonstrating ownership of platform products used by multiple teams.
• Proven ability to design, operate, and scale build systems for complex, large-scale products that span both cloud and embedded device contexts.
• Experience making architectural trade-offs that balance speed, maintainability, and organizational scale while managing technical debt responsibly.
• Working knowledge of secure software delivery practices, including policy enforcement, vulnerability management, and compliance frameworks relevant to AI products.
• Ability to work in a hybrid model with four days per week in the San Francisco office, fostering close collaboration and in-person alignment with cross-functional partners.
• Strong experience with version control systems, build tools, and infrastructure automation at scale, ensuring reproducibility and reliability.
• Demonstrated skill in debugging complex issues in distributed systems, using logs, metrics, and traces to identify root causes efficiently.

Nice to have

• Experience with Kubernetes, Terraform, Buildkite, Bazel, Postgres, Cosmos DB, and Kafka, providing hands-on familiarity with the tools that power the platform.
• Background in consumer hardware or embedded systems software, offering insight into the constraints and requirements of device-level integration.
• Familiarity with AI tooling and workflows, including model training, inference, and evaluation pipelines, to better support AI-driven product teams.
• Contributions to open source projects or internal platform tooling, showing initiative in improving developer workflows and infrastructure reliability.
• Experience with monitoring, observability, and alerting systems, enabling data-driven decisions that improve platform health and performance.
• A history of mentoring engineers through code reviews, design discussions, and technical coaching, elevating the overall engineering bar.

Practical notes

OpenAI provides relocation assistance for new hires. The role requires an on-site presence four days per week. Background checks are conducted in accordance with local laws, including the San Francisco Fair Chance Ordinance. Reasonable accommodations are available for applicants with disabilities. Applications will be reviewed on a rolling basis until the position is filled. Candidates are encouraged to submit complete applications that clearly demonstrate relevant experience and alignment with the role expectations.