WHAT YOU'LL DO
Own end-to-end execution of critical company programs, working with engineering, product, and business leaders to define outcomes, scope, owners, milestones, and success metrics. Focus your efforts where they can have the greatest impact as company priorities evolve.
Lead programs across technical domains. Examples could include AI infrastructure: coordinating capacity planning with engineering, finance, and model providers; driving model failover readiness; and enabling model experiments that evaluate quality, latency, reliability, and cost.
Drive developer productivity programs, such as evaluating and scaling AI coding agent usage, improving test coverage and reliability, and reducing CI/CD bottlenecks. Measure their impact on engineering velocity, software quality, and release safety.
Drive product-facing programs, such as launching new AI-powered workflows, coordinating capabilities that span multiple product teams, or improving end-to-end product performance and reliability. Align engineering, product, design, and go-to-market partners on launch readiness and customer outcomes.
Surface risks and systemic gaps early, resolve ownership gaps, and sequence dependencies across teams. Partner with senior engineers and engineering managers to evaluate technical tradeoffs and unblock decisions.
Build a lightweight operating cadence that makes progress, risks, and decisions clear to teams and leadership. Define and track program-specific metrics, and follow through after launch to ensure sustained impact.
Create alignment across functions and levels of the organization, translating complex technical issues into clear decisions and escalating when priorities, resources, or dependencies put outcomes at risk.
WHAT YOU HAVE
7+ years of experience in technical program management, with a track record of delivering large, ambiguous programs across multiple teams and technical domains.
Strong technical judgment and the ability to ramp quickly across unfamiliar parts of the stack, from infrastructure and AI systems to developer tooling and customer-facing applications. You can read system designs critically, ask substantive questions, and help teams reason through tradeoffs.
Demonstrated ability to lead and influence engineering stakeholders — senior ICs, EMs, and execs — without direct authority.
Excellent written and verbal communication, with a particular ability to distill complex technical tradeoffs into crisp narratives for both technical and cross-functional audiences.
A track record of building durable mechanisms (review forums, metrics, operating cadences) that outlive any individual program.
Comfort with ambiguity. You're energized by problems that aren't yet well-defined and where the first step is to scope the problem itself.
Bachelor's degree in Computer Science, Engineering, or related technical field.
BONUS POINTS
Hands-on experience in software engineering, AI/ML infrastructure, developer platforms, SRE, or technical product delivery.
Experience with AI model capacity planning, provider integrations, model evaluation and experimentation, or reliability and failover programs.
Experience evaluating and scaling AI coding agents or other developer tools, or leading improvements in testing, CI/CD, and release safety, with measurable impact.
Experience delivering customer-facing products or major launches that require coordination across engineering, product, design, and go-to-market teams.
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We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai
