AI Program Manager Jobs

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Build and scale the systems that power model and product evaluations across Harvey; run intake, triage, and prioritization for the evaluation request queue, routing capacity to the highest-value coverage gaps; embed evaluation workflows and readiness checkpoints into the product development lifecycle; create the single source of truth for evaluation status, results, history, and launch readiness; turn Expert-designed evaluation methodologies into scalable, repeatable operational processes; manage human data providers and stand up the internal contract-attorney pipeline, ensuring evaluation quality meets legal standards; work with Engineering and Research to improve evaluation tooling, automation, and dashboards; drive evaluation readiness for major product and model launches across geographies and jurisdictions; document and operationalize evaluation governance as complexity increases; help define how Harvey ensures model accuracy, reliability, and trust at global scale.

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As a Production AI Ops Lead, you will design and develop the production lifecycle of full-stack AI applications, while supporting end-to-end system reliability, real-time inference observability, sovereign data orchestration, high-security software integration, and the resilient cloud infrastructure required for international government partners. You will take full accountability for the long-term performance and reliability of AI use cases deployed across international government agencies. You will oversee the end-to-end health of the platform, ensuring seamless integration between the AI core and all full-stack components, from APIs to UI, to maintain a responsive and production-ready environment. You will build automated systems to monitor model performance and data drift across geographically dispersed environments, ensuring the right levels of reliability. You will manage the technical lifecycle within diverse regulatory frameworks. You will lead the response for production issues in mission-critical environments, ensuring rapid resolution and building guardrails to prevent recurrence. You will translate deep technical performance metrics into clear insights for senior international government officials. You will also partner with Engineering and ML teams to ensure lessons learned in the field influence the technical architecture and decisions of future use cases.

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Lead the Command Center Insights & Actions team to build systems that translate raw infrastructure telemetry into human-readable diagnostics and automated remediation workflows. Own and execute a technical roadmap including alerting engines, heuristic development, node health systems, and state machines that trigger proactive maintenance without impacting customer workloads. Explore integration of Large Language Models to build AI solutions within the Command Center product. Drive the Insights & Actions roadmap covering alerting infrastructure, control plane APIs, automated action systems, and telemetry-derived insights such as straggler node detection and GPU profiling. Contribute to strategic roadmaps, refine early product requirements, collaborate cross-functionally with product, design, and engineering teams, manage complex multi-engineer projects focused on customer outcomes, drive technical excellence through process improvements and best practices, and cultivate team growth by coaching and mentoring engineers, setting clear performance expectations, and defining career paths to build a high-performing and sustainable team.

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Lead, hire, and mentor a team of AI Deployment Engineers supporting Codex customers across strategic accounts; own the operating model and engagement strategy for Codex deployment efforts to ensure customers move from pilot to production adoption; guide teams in designing and implementing AI-enhanced development workflows, automations, and scalable deployment architectures; act as the senior technical escalation point for complex customer implementations and deployment challenges; partner with Sales, Product, Research, and Applied Engineering teams to align customer outcomes with product direction and roadmap priorities; help establish repeatable deployment playbooks, technical patterns, and best practices for scaled adoption of AI coding tools; coach engineers to serve as trusted advisors to engineering leadership and executive stakeholders; synthesize insights from customer deployments into actionable feedback for internal teams; champion safe, reliable, and effective adoption of AI-powered development workflows across industries.

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Lead, hire, and mentor a high-performing team of AI Deployment Engineers supporting Codex customers across strategic accounts. Own the operating model and engagement strategy for Codex deployment efforts, ensuring customers successfully move from pilot to production adoption. Guide teams in designing and implementing AI-enhanced development workflows, automations, and scalable deployment architectures. Act as the senior technical escalation point for complex customer implementations and deployment challenges. Partner with Sales, Product, Research, and Applied Engineering teams to align customer outcomes with product direction and roadmap priorities. Help establish repeatable deployment playbooks, technical patterns, and best practices that enable scaled adoption of AI coding tools. Coach engineers to operate as trusted advisors to engineering leadership and executive stakeholders. Synthesize insights from customer deployments and translate them into actionable feedback for internal teams. Champion safe, reliable, and effective adoption of AI-powered development workflows across industries.

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As a Production AI Ops Lead on Scale's Global Public Sector team, you will design and develop the production lifecycle of full-stack AI applications, support end-to-end system reliability, real-time inference observability, sovereign data orchestration, high-security software integration, and resilient cloud infrastructure for international government partners. You will take full accountability for the long-term performance and reliability of AI use cases deployed across international government agencies, oversee the end-to-end health of the platform to ensure seamless integration between AI core and full-stack components including APIs and UI, build automated systems to monitor model performance and data drift across geographically dispersed environments, manage the technical lifecycle within diverse regulatory frameworks, lead incident response for production issues in mission-critical environments ensuring rapid resolution and prevention measures, translate deep technical performance metrics into clear insights for senior international government officials, and collaborate with Engineering and ML teams to ensure field lessons influence future technical architecture and decisions.

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Lead and scale the Startups AI Deployment Engineering team to help high-growth startups move from experimentation to production and build technical partnerships with OpenAI. Craft and refine the strategic vision and operating model for the team aligned with company objectives and startup needs. Mentor and grow a team of technical individual contributors supporting startup customers across various company types. Identify technical blockers for startups, advise on architecture, and drive practical deployment. Partner with Sales to prioritize technical engagement for adoption and account growth. Represent startup customer technical feedback, focusing on developer experience, product gaps, and deployment challenges. Develop repeatable deployment playbooks, starter packs, reference architectures, and tools to accelerate team efficiency. Serve as a senior technical escalation point, including for executive-level conversations. Balance urgent startup requests with OpenAI’s broader product and platform priorities. Coach engineers on quality, judgment, communication, and cross-functional partnership. Collaborate across Sales, Product, Engineering, Research, and GTM teams to improve startup support from adoption through production usage.

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The AI Engineering Lead is responsible for staying up-to-date on the latest AI technology and collaborating with engineering teams to advance product capabilities, defining and implementing the future of the AI Engineering function at the company as it scales, hiring and mentoring a team of AI Engineers, supporting an exceptional developer and research experience for teams working with AI technology, and delivering high-performing shared AI infrastructure, including search systems.

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The AI Deployment Engineering Manager in Korea is responsible for owning the strategy and operating model of the AI Deployment Engineering team to ensure alignment with company objectives and customer needs. They lead, build, and mentor a team of AI Deployment Engineers to deliver exceptional customer results, as measured by production customer applications and API adoption. The role involves serving as the technical advocate for customers by synthesizing their needs to inform research and product/engineering roadmaps, acting as the primary technical escalation point during development, maintaining direct communication with executive-level stakeholders, and serving as an industry thought leader to champion the safe and innovative use of the technology across sectors.

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As an AI Operations Lead at Broccoli AI, the role involves building internal systems to enable company scaling, including developing dashboards that provide clear visibility into key metrics for different teams, designing and deploying AI agents that automate repetitive tasks across sales, customer success, and operations, and creating internal tools and workflows to remove bottlenecks. The role includes partnering with team leads to prioritize high-leverage automation opportunities, setting up evaluation, monitoring, and iteration processes to ensure AI agents remain reliable in production, and helping define internal operational procedures as the company grows.