AI Deployment Engineering Manager, Startups
Leads and scales a customer-facing Applied AI Engineering team serving high-growth startups, guiding customers from experimentation to production while building repeatable deployment mechanisms. Requires technical depth in AI/ML platforms and experience leading teams in startup-focused, ambiguous environments.
About the job
Responsibilities
- Define and refine the strategic vision and operating model for the Startups Applied AI Engineering team.
- Lead, mentor, and grow high-performing technical individual contributors supporting startup customers.
- Help startups move from experimentation to production by identifying technical blockers, advising on architecture, and driving deployment.
- Partner with Sales to accelerate adoption, production usage, and account growth.
- Represent startup customers by synthesizing feedback on developer experience, product gaps, deployment blockers, model performance, and emerging use cases.
- Develop repeatable playbooks, starter packs, reference architectures, internal tooling, and customer-facing assets.
- Serve as a senior technical escalation point for priority startup customers and executive-level conversations.
- Balance urgent customer needs with broader product and platform priorities.
- Coach engineers on technical quality, customer judgment, prioritization, executive communication, and cross-functional collaboration.
- Partner with Sales, Product, Engineering, Research, and go-to-market teams to improve startup support from adoption through scaled production.
Requirements
- Experience founding, scaling, or operating within early-stage startups, ideally in technical leadership roles spanning product or customer outcomes and technical execution.
- Experience building and leading technical, customer-facing teams in high-growth, ambiguous, or startup-focused environments.
- Strong technical depth across APIs, platform products, AI/ML systems, developer workflows, and production deployment.
- Experience creating scalable operating models rather than managing only one-off customer escalations.
- Comfort working directly with founders, CTOs, technical executives, and highly technical individual contributors.
- Strong judgment in balancing deep engagement for strategic customers with repeatable mechanisms for broader coverage.
- Ability to translate complex technical and product considerations into clear decisions, practical guidance, and customer recommendations.
- Ability to operate quickly and pragmatically while maintaining quality, safety, and long-term platform strategy.
- Commitment to the safe and beneficial development of AI.
Success Measures
- Increased startup account usage, including tokens, requests, and production workloads.
- Successful customer sprints and production-focused technical engagements.
- High-quality customer stories, executive satisfaction, and referenceable startup wins.
- Repeatable startup deployment patterns, starter packs, templates, and reference architectures.
- Strong Product and Research feedback loops based on startup needs and emerging use cases.
- A healthy, high-performing team with clear prioritization and scalable operating mechanisms.
Compensation
- Annual salary range: $251,000–$335,000.
Skills
APIs, Ai/Ml Systems, Production Deployment, Developer Workflows, Platform Products, Architecture, Reference Architectures, Internal Tooling, Cross-Functional Collaboration, Executive Communication
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