Senior Forward Deployed Applied Scientist I (Agentic AI)

Dive in and do the best work of your career at DigitalOcean. Journey alongside a strong community of top talent who are relentless in their drive to build the simplest scalable cloud. If you have a growth mindset, naturally like to think big and bold, and are energized by the fast-paced environment of a true industry disruptor, you’ll find your place here. We value winning together—while learning, having fun, and making a profound difference for the dreamers and builders in the world. Position Overview The Forward Deployed AI (FDE) team operates at the intersection of AI research, production deployment, and customer impact. As an Agentic AI Applied Scientist, you won't sit in an isolated research lab—you will embed directly with high-growth startups, tech innovators, and AI native enterprise partners. You will design, build, and deploy custom autonomous agent architectures running on DigitalOcean’s high-performance AI infrastructure. What You’ll Do Architect Production-Ready Agentic Frameworks: Design and implement sophisticated multi-agent workflows, autonomous reasoning loops, and tool-augmented LLM architectures capable of resolving complex, real-world customer challenges. Direct Customer Integration: Embed deeply with tech innovators, CTOs, and AI engineering leads to transform ambiguous business requirements into high-performance, deterministic AI/Agentic workflows. Synthesize Research and Deployment: Quickly prototype cutting-edge agentic frameworks—leveraging LangGraph, AutoGen, or custom execution graphs—and harden them for enterprise-scale production and stateful memory retention. Drive Reliability and Evaluation: Develop comprehensive reusable Evals frameworks and safety guardrails to monitor reasoning precision, execution security, latency, and cost-efficiency across agentic systems. Optimize the DigitalOcean Ecosystem: Serve as a strategic feedback link between our customers and core AI/ML Product teams, converting field deployment friction into foundational platform enhancements. Travel & Collaboration Requirements: Ability to travel up to 30% for customer engagements, strategic workshops, conferences, and internal collaboration. Ability to consistently overlap with North American business hours, including availability until at least noon Eastern Time, to collaborate effectively with customers, Product, Engineering, and go-to-market teams. What You’ll Add to DigitalOcean 4+ years of hands-on experience in Applied AI, Machine Learning, or Data Science. Expertise in Multi-agent Frameworks: Proven experience building multi-agent orchestration engines, tool-use / function-calling pipelines, MCP, structured outputs, dynamic planning, and persistent memory models. Production Python & Systems Engineering: Strong skills in writing clean, production-ready Python (Pydantic, FastAPI, Asyncio, PyTorch). Customer-Facing Engineering Mindset: High empathy, crisp technical communication, and the ability to articulate complex AI trade-offs to both engineering leads and executive sponsors. The DO "Shark" Mentality: You think big, bold, and scrappy. You have a bias for action and a powerful sense of ownership over the customer experience. Preferred Qualifications Education: Ph.D. or Master’s degree in Computer Science, Machine Learning, AI, or a related technical field. Applied Science Experience: Experience in deep learning frameworks (like PyTorch or TensorFlow), distributed training tools as well as various agentic AI frameworks. Solid understanding of various types of transformers and state space models. Research Experience: Experience in publications, patents and Knowledge of latest research in the field of LLM, VLM, Agentic frameworks. Customer Empathy & Technical Leadership: Ability to translate complex business tasks into AI engineering solutions and collaborate directly with client teams (CTOs, AI Leads). Agility: Comfortable navigating fast-moving environments and tuning model workloads for diverse accelerator architectur…