Forward Deployed Applied Scientist ; Agentic AI

Dive in and do the best work of your career rney 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.

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 Digital Ocean’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 Lang Graph, Auto Gen, 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 Digital Ocean Ecosystem:
  Serve as a strategic feedback link between our customers and core AI/ML Product teams, converting field deployment friction into foundational platform enhancements.
• Platform Validation & Product Acceleration:
  Act as the “first customer” for Digital Ocean’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.
• Travel & Collaboration Requirements:
  Ability to travel up to 30% for customer engagements, strategic workshops, conferences, and internal collaboration.

• 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.

• 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 Tensor Flow), 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…