Why This Job is Featured on The SaaS Jobs
This Power Architect role stands out in the SaaS landscape because it sits at the infrastructure layer that increasingly determines what AI-enabled software can deliver. While the listing is hardware-focused, the remit is explicitly tied to deployment-grade systems that support large-scale AI workloads, linking silicon decisions to real product constraints like reliability, throughput, and energy use. That connection matters as more SaaS companies differentiate through model performance and cost-to-serve, not just features.
Career-wise, the position builds rare cross-stack fluency that translates across modern SaaS organizations running intensive compute. Ownership of power modeling, telemetry, and power management features develops a systems view of how workloads behave in production and how efficiency levers are prioritized. The collaboration surface spans architecture, kernels, firmware, platform design, and external vendors, offering a strong template for influencing technical roadmaps where hardware and software are co-designed.
This role is best suited to practitioners who prefer hands-on technical depth and can navigate ambiguity across disciplines without relying on narrow ownership boundaries. It fits someone motivated by measurement-driven tradeoffs and long planning horizons, and who wants their work to shape the operational economics behind AI products rather than only the application layer.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
About the Team
OpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI’s supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI.
About the Role
We are seeking a highly skilled cross-stack power architect with deep expertise in making ML systems energy efficient. This hands-on individual contributor will sit within our silicon implementation team and work closely with architecture, kernels, chip design, silicon implementation, platform design, and the broader industry ecosystem to architect, implement, and deploy performance-per-watt optimized next-generation AI accelerator chips and systems.
In this role, you will:
Oversee power architecture, implementation, and execution in silicon from concept to high-volume deployment, and propose high-ROI features to maximize performance under power envelope
Build chip and system-level power models grounded in empirical data and experience to guide organization-wide energy efficiency strategy. This requires a detailed understanding of ML workloads, ML chip and system architecture, silicon design, implementation, and characterization
Collaborate with chip and platform architecture/design teams to explore and implement power management features, including the specification and implementation of digital/mixed-signal IP, sensing and telemetry, firmware/system software, and silicon characterization methodology (in partnership with engineering teams)
Partner with silicon design and implementation teams, to optimize performance under power envelope. This includes (but is not limited to) clocking and power domain architecture, voltage/frequency selection, microarchitecture and physical-design driven power reduction, post-silicon voltage margin optimization and workload-informed power optimization
Work with ecosystem partners (EDA, ASIC, IP, component vendors) to drive innovations that can improve energy efficiency
Qualifications:
Relevant degree and strong industry experience focused on the end-to-end energy-efficient ML silicon codesign
Hands-on experience with power architecture, power estimation, power management and power optimization is required.
Fundamental understanding of ML chip and platform architecture, performance modeling and workload power/performance characteristics is strongly preferred.
Hands-on experience with power bring-up and power validation is strongly preferred.
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.
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