Applied AI Engineering Manager, Startups | Greenfield
- Market p25–p75
- £88k–£240k
- H-1B median · ML / AI
- $250k
- Opened · 30d
- +88
- Closed · 30d
- −67
- Opened · 7d
- +118% of open
- All ml / ai
- 6,614open
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, Greenfield to lead and scale our Applied AI Engineering team. Greenfield encompasses two complementary motions: helping early-stage startups reach their first meaningful production deployment and initial scale, and winning high-potential startups through competitive evaluations and migrations. Depending on the team you lead, you will coach engineers towards scalable activation or deep, targeted technical pursuits.
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 unlock outsized 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 architecture, and driving practical paths to deployment. Lead technical strategy for priority competitive pursuits, coaching engineers on workload discovery, representative evaluations, quality and cost optimisation, and migration planning.
Partner 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.
Balance urgent customer needs with OpenAI’s broader product and platform priorities, especially when startups request niche features, bespoke support, or accelerated roadmap changes.
Coach Applied AI Engineers on technical quality, customer judgment, prioritization, executive communication, and cross-functional partnership.
Work closely with VC Partnerships, Marketing, and developer-facing teams to turn ecosystem relationships and programmes into technical engagement, first production deployments, and sustained adoption. Build repeatable technical programmes, workshops, and starter patterns that expand the team’s reach.
You might thrive in this role if you
Have proven experience founding, scaling, or operating within early-stage startups, ideally in technical leadership roles where you owned both product or customer outcomes and technical execution.