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NEXTMOVEFDE careers · United States

Manager, Applied AI Engineering (Startups)

No longer in the current catalog. Last included 2026-09-09. Check the employer’s posting for availability.

Technologies

APIs · AI/ML systems · developer workflows · production deployment · reference architectures · internal tooling · model performance · GPT

About OpenAI

Builds frontier AI models (GPT series) and ships them as ChatGPT consumer/enterprise products plus a developer API for the broader AI ecosystem.

Private Late

Job description

The full responsibilities and requirements are on the employer’s site.

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Source and classification

Internal deployment & tooling · Evidence for this classification:

About the Team The Applied AI Engineering team partners closely with customers to help them move from experimentation to production with OpenAI’s technologies. We act as trusted technical advisors, working across customer strategy, architecture, deployment, and adoption to help organizations realize meaningful impact from frontier AI. The Startups segment serves fast-moving, high-growth companies that are often building new products, workflows, and businesses directly on top of AI. These customers move quickly, operate with high ambiguity, and expect practical, creative, and technically rigorous partnership. About the Role We are looking for an Applied AI Engineering Manager, Startups to lead and scale the Startups Applied AI Engineering motion. This team helps high-growth startups move quickly from experimentation to production, unlock meaningful usage, and build durable technical
More from the job description

About the Team The Applied AI Engineering team partners closely with customers to help them move from experimentation to production with OpenAI’s technologies. We act as trusted technical advisors, working across customer strategy, architecture, deployment, and adoption to help organizations realize meaningful impact from frontier AI. The Startups segment serves fast-moving, high-growth companies that are often building new products, workflows, and businesses directly on top of AI. These customers move quickly, operate with high ambiguity, and expect practical, creative, and technically rigorous partnership. About the Role We are looking for an Applied AI Engineering Manager, Startups to lead and scale the Startups Applied AI Engineering motion. This team helps high-growth startups move quickly from experimentation to production, unlock meaningful usage, and build durable technical partnerships with OpenAI. This leader will operate in a high-velocity customer segment where founders, CTOs, and technical teams expect speed, judgment, and hands-on problem-solving. They will balance team leadership, technical depth, customer prioritization, and cross-functional influence across Sales, Product, Engineering, Research, and broader go-to-market teams. In this role, you will define how OpenAI supports startup customers at scale: identifying where deep technical engagement can unlo [... source excerpt omitted ...] ized impact, building repeatable deployment mechanisms, and ensuring the team can serve a broad and dynamic customer base without losing quality or strategic focus. In this role, you will: Craft and continuously refine the strategic vision and operating model for the Startups Applied AI Engineering team, aligning it with OpenAI’s broader company objectives and the evolving needs of high-growth startup customers. Lead, mentor, and grow a team of high-performing technical ICs supporting startup customers across AI-native, developer-led, and product-led companies. Help startups move from early experimentation to production usage by identifying technical blockers, advising on arc [... source excerpt omitted ...] rtner closely with Sales to determine where technical engagement can accelerate adoption, production usage, and long-term account growth. Represent the technical voice of startup customers by synthesizing high-signal feedback, especially around developer experience, product gaps, deployment blockers, model performance, and emerging use cases. Translate recurring startup needs into repeatable playbooks, starter packs, reference architectures, internal tooling, and customer-facing assets that help the broader team move faster. Serve as a senior technical escalation point for priority startup customers, including founder-, CTO-, and technical executive-level conversations. Balan

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