Forward Deployed Applied Scientist I (Agentic AI)

DigitalOcean • Seattle, WA

1d • Hybrid

About The Position

The Forward Deployed Engineering (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.

Requirements

• 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.

Nice To Haves

• Ph.D. or Master’s degree in Computer Science, Machine Learning, AI, or a related technical field.
• 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.
• Experience in publications, patents and Knowledge of latest research in the field of LLM, VLM, Agentic frameworks.
• Ability to translate complex business tasks into AI engineering solutions and collaborate directly with client teams (CTOs, AI Leads).
• Comfortable navigating fast-moving environments and tuning model workloads for diverse accelerator architectures.
• Experience collaborating with customers, model vendors, or ecosystem partners on benchmarking, optimization, finetuning, or launch readiness initiatives.

Responsibilities

• Design and implement sophisticated multi-agent workflows, autonomous reasoning loops, and tool-augmented LLM architectures capable of resolving complex, real-world customer challenges.
• Embed deeply with tech innovators, CTOs, and AI engineering leads to transform ambiguous business requirements into high-performance, deterministic AI/Agentic workflows.
• Quickly prototype cutting-edge agentic frameworks—leveraging LangGraph, AutoGen, or custom execution graphs—and harden them for enterprise-scale production and stateful memory retention.
• Develop comprehensive reusable Evals frameworks and safety guardrails to monitor reasoning precision, execution security, latency, and cost-efficiency across agentic systems.
• Serve as a strategic feedback link between our customers and core AI/ML Product teams, converting field deployment friction into foundational platform enhancements.
• Act as the “first customer” for DigitalOcean’s AI-native platform capabilities including Inference Engine, runtimes, orchestration systems, GPU platforms, and deployment workflows.
• Surface real-world operational insights, architectural gaps, and scaling bottlenecks directly to Product Engineering and Research teams.
• Ability to travel up to 30% for customer engagements, strategic workshops, conferences, and internal collaboration.

Benefits

• Employee Assistance Program
• Local Employee Meetups
• flexible time off policy
• reimbursement for relevant conferences, training, and education
• LinkedIn Learning's 10,000+ courses
• bonus in addition to base salary
• equity compensation to eligible employees, including equity grants upon hire and the option to participate in our Employee Stock Purchase Program

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level