Technical Program Manager

DigitalOcean•Seattle, WA

6h•$148,800 - $186,000•Hybrid

About The Position

As a Technical Program Manager on the Agentic AI team, you will drive value delivery for a set of technical programs that bring our AI-powered products and platform capabilities to life — spanning agentic systems, LLM-powered features, AI infrastructure, and the developer tooling that enables builders to ship intelligent applications. This individual will be an experienced cross-functional leader who champions continuous improvement and thrives in a fast-paced environment, applying technical literacy along with program management experience to navigate delivering on commitments as a leader on their team. In this role, you will partner with Product, Engineering, and AI research leaders to drive the delivery of valuable, often complex, technical programs that advance our Agentic AI Cloud and meet our customers’ rapidly evolving AI needs. You will be the connective tissue across model teams, platform engineering, developer experience, and outside partners — embodying servant leadership to ensure efficient, effective value delivery. You will be a proactive collaborator while driving consensus where needed and influencing decisions when teams are stuck.

Requirements

10+ years of experience as a Technical Program Manager delivering cross-functional programs in a fast-paced environment, with a preference for experience in AI/ML, platform engineering, or developer tooling
Proven track record planning and delivering complex programs, leading the resolution of blocking issues, and driving effective change management
Solid understanding of AI/ML fundamentals — model training vs. inference, agentic architectures, LLM APIs, and the emerging landscape of AI developer tooling — and how these translate into real product and platform decisions
Hands-on familiarity with agentic AI concepts, including multi-step reasoning, tool use, retrieval-augmented generation (RAG), and the orchestration frameworks (e.g., LangChain, LlamaIndex, or similar) builders use to create intelligent applications
Experience coordinating external model providers, API partners, and open-source communities to deliver AI-powered product capabilities
Strong risk management skills, with a proven ability to spot risks early — a model capability gap, an inference latency constraint, or a shifting vendor dependency — and build plans to keep programs moving
Ability to influence and work through others where direct reporting relationships do not exist, acting as a reliable bridge between deeply technical AI teams and product and operational teams
Ability to distill complex or technical concepts — including nuanced AI/ML tradeoffs — into clear, structured communications and action plans
Ability to balance a detail- and process-oriented mindset with a focus on outcomes
Experience with project management tooling (e.g., the Atlassian suite — Jira and Confluence) for managing the flow of value and delivering curated information to appropriate stakeholders
Embraces AI as a force multiplier — actively using AI tools and agentic workflows to work faster and smarter, with a continuous eye for where AI can improve how programs get delivered and how the team operates
A growth mindset that prioritizes learning and improvement for yourself and the teams you work with

Responsibilities

Drive value delivery for major Agentic AI programs — spanning model integrations, agentic framework development, AI platform capabilities, and developer tooling — including prioritization, planning, risk management, execution, and measurement of success
Partner with Product, Engineering, and AI research leaders, including senior leaders, throughout the life of the program on value delivery and process/practice improvements
Act as the central hub of communication, keeping model teams, platform engineers, developer experience teams, and external AI partners aligned to keep programs on track
Coordinate the steps from early capability planning and prototyping through production deployment, partnering with model providers, inference infrastructure teams, and internal platform teams
Drive decision-making across multiple teams, orgs, and stakeholders spanning multiple locations, including with senior leaders
Proactively manage changes in scope and priority shifts; recognize risk early — whether a model capability gap, a latency constraint, or a shifting API dependency — and form mitigation plans as required
Build repeatable, scalable processes — and the visibility and operational infrastructure behind them — that get AI capabilities to market faster, improve reliability, and ensure effective, sustainable operations across teams and orgs
Evangelize technical project & program management best practices within their team and across partner teams and orgs