Director of Research, Agentic AI

DigitalOcean•Seattle, WA

56d•$249,600 - $312,000•Hybrid

About The Position

DigitalOcean is building the Agentic Inference Cloud, anchored by Inference Engine, our model-serving platform, to help fast-growing AI-native companies start, scale, and optimize agentic workloads. Applied Research is the layer that generates the proprietary science that compounds across that platform, focusing on areas like adaptive routing, memory improvement, agent observability, and reinforcement learning. We are seeking a Director of Research to build and lead this function, setting the research agenda, growing the team, and ensuring the science produced translates into real product outcomes such as improved model selection, more reliable agents, reduced cost and latency, and higher task-success rates for users of DigitalOcean's platform. This is a hybrid role that requires both technical depth to guide research direction in key areas and leadership capabilities to build a team, manage a roadmap, and advocate for research investment.

Requirements

10+ years in applied ML/AI research or research-adjacent engineering.
Experience leading a research team or function (formal people management or de facto technical leadership).
Deep, hands-on expertise in at least two of the following areas: LLM routing and model selection, retrieval and memory systems, agent observability and evaluation, or reinforcement learning (RLHF, RLAIF, DPO, PPO, GRPO, or related methods).
A track record of shipping research into production systems.
Fluency with the current agentic AI landscape, including reasoning, planning, tool use, long-horizon memory, and the practical economics of large-scale model serving.
Strong technical communication skills, with the ability to defend a research agenda and translate ambiguous research questions into a roadmap with concrete checkpoints.

Nice To Haves

Experience building or scaling an applied research team within a product organization.
Direct experience with inference infrastructure or large-scale model-serving optimization.
Familiarity with the broader open-weight and open-source model ecosystem.
PhD in CS, ML, or a related field, or equivalent depth demonstrated through industry impact.
Publications, patents, or open-source contributions in routing, memory, agent evaluation, or reinforcement learning.
Experience with small, specialized models or domain-tuned LLMs.

Responsibilities

Set the research agenda and define the applied research roadmap across adaptive routing, memory systems, agent observability, and reinforcement learning.
Track emerging model architectures and specialized model approaches, translating relevant findings into DigitalOcean's product roadmap.
Ensure research efforts are tightly coupled to product outcomes, with each research bet mapping to measurable improvements in key performance indicators.
Grow the Applied Research team by hiring and mentoring research scientists and engineers.
Establish the team's operating rhythm, including scoping research questions, running and evaluating experiments, and managing handoffs to production teams.
Represent Applied Research in cross-functional planning, advocating for headcount and investment.
Partner with Inference Engine and other platform/product engineering teams to integrate research into shipped capabilities.
Transform research prototypes into production-ready features in collaboration with engineering.
Clearly communicate research trade-offs to non-research stakeholders.
Build DigitalOcean's credibility in the applied agentic-AI research community through publications, talks, open-source contributions, or collaborations.