AI Development & Support Engineer

Starfish Storage Corporation•Waltham, MA

12d•Hybrid

About The Position

Starfish manages petabytes of unstructured data for national labs, research institutions, fintech, and pharma, the kind of data that doesn't fit neatly into databases or cloud buckets. We're building an AI-native layer on top of that: MCP servers, agentic workflows, local LLM deployments, and tools that let researchers and engineers actually talk to their storage infrastructure. We're tackling hard questions too: should an agent be permitted to move 2PB of data autonomously? How do you govern that? In this role, you'll build and ship MCP servers, deploy and tune local LLMs, write custom agents for real customers with real petabyte-scale problems, and get them running in environments where "just use the API" isn't an option. You'll also support customers when things don't work: which means you need to actually understand what you've built.

Requirements

Solid grasp of agent architectures, prompt engineering, and MCP or tool-use patterns
Hands-on experience with local/open-source LLMs: you've run them, tuned them, deployed them
Comfortable working in Linux environments and debugging at the command line
Strong communicator: you can explain what's broken and why to both engineers and non-engineers
Real experience implementing AI solutions, not just trying out tutorial videos
Ability to context-switch between deep development work and supporting a customer mid-debug
Comfortable being the person who figures things out when there's no playbook yet

Nice To Haves

2+ years Python development — real shipped and used code
Experience with RAG pipelines or vector databases
Familiarity with REST APIs and integration patterns
Docker comfort
Background in storage systems or HPC environments

Responsibilities

Build and expand MCP servers that expose Starfish's data management capabilities to LLM-powered workflows
Develop intelligent agents that can reason over storage metadata at scale — including local LLM deployment and configuration using vLLM, Ollama, or similar
Create workflow automation and chat-based interfaces for querying and acting on Starfish data
Build proof-of-concept implementations and turn them into production-grade features
Support customers through installation, configuration, and troubleshooting of AI features and integrations
Get on calls with technical teams, understand their use cases, and translate requirements into working agents
Document what you learn so the next person doesn't have to figure it out from scratch