Staff Forward Deployed Applied Scientist (Agentic AI)
$220k - $239k • Seattle • Full-time
Posted 5mo ago
This job has been open for more than 60 days. It may no longer be actively hiring, so check with the company before putting a lot into an application.
Job Location
Seattle
Also open in San Francisco
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Agent Engineer
About the job
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 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. This role involves architecting production-ready agentic frameworks, directing customer integration, synthesizing research and deployment, and driving reliability and evaluation of AI systems.
Responsibilities
- Design and implement sophisticated multi-agent workflows, autonomous reasoning loops, and tool-augmented LLM architectures.
- Embed with tech innovators, CTOs, and AI engineering leads to transform business requirements into AI/Agentic workflows.
- Quickly prototype cutting-edge agentic frameworks and harden them for enterprise-scale production.
- Develop comprehensive Evals frameworks and safety guardrails for agentic systems.
- Serve as a feedback link between customers and AI/ML Product teams, converting field friction into platform enhancements.
- Act as the “first customer” for DigitalOcean’s AI-native platform capabilities and surface operational insights.
- Travel up to 30% for customer engagements, workshops, conferences, and internal collaboration.
Requirements
- 8+ years of hands-on experience in Applied AI, Machine Learning, or Data Science.
- Proven experience building multi-agent orchestration engines, tool-use / function-calling pipelines, MCP, structured outputs, dynamic planning, and persistent memory models.
- Strong skills in writing production-ready Python (Pydantic, FastAPI, Asyncio, PyTorch).
- High empathy, crisp technical communication, and ability to articulate complex AI trade-offs.
- Experience in deep learning frameworks (like PyTorch or TensorFlow), distributed training tools, and agentic AI frameworks.
- Solid understanding of various types of transformers and state space models.
- Experience in publications, patents and knowledge of latest research in LLM, VLM, Agentic frameworks.
- Ability to translate complex business tasks into AI engineering solutions and collaborate directly with client teams.
- 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.
Benefits
- Flexible time off
- Local team meetups
- Mental health and well being support
- Reimbursement for relevant conferences, training, and education