AI Development & Support Engineer

How to Apply

Provide the following required materials:

• Resume
• Cover Letter In your application you must submit a cover letter. Please provide brief concrete examples for the following questions. We value specific technical details tool names and honest assessments of where technology succeeds and fails.

1. Describe a project where you used an AI tool (e.g. ChatGPT Claude Cursor GitHub Copilot etc) to write or significantly speed up your coding. What were you building what was your specific approach to instructing the AI and where did the AI fall short
2. All LLMs have specific coding quirks and repetitive errors. Name the specific model you use most (e.g. Opus GPT-5.x) and describe a highly specific recurring syntax or logic error it makes that drives you crazy. How do you work around it
3. If a hot new open-source AI model gets released tomorrow and you want to test it out locally on your own laptop or machine (not just using a web browser) how would you set that up What specific software tools or frameworks would you use to get it running

Location

Your home office or our Waltham MA HQ or hybrid

Qualifications

Hard Requirements

• Solid grasp of agent architectures prompt engineering and MCP or tool-use patterns
• Hands-on experience with local/open-source LLMs: youve run them tuned them deployed them
• Comfortable working in Linux environments and debugging at the command line
• Strong communicator: you can explain whats broken and why to both engineers and non-engineers
• This is not a role for someone who has tried out some youtube tutorial videos on their own. You need to have some real experience implementing this.

Helpful Background

• 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 (this helps more than you think)

Working Style

• You can context-switch between deep development work and supporting a customer mid-debug
• Youre comfortable being the person who figures things out when theres no playbook yet

About Starfish Storage

Starfish Storage is an established company that maintains a startup culture mindset. We cater to a diverse client base serving industries such as life sciences artificial intelligence and research computing. Our technology is critical to modern organizations helping customers organize manage and move the tens of billions of files central to their operations.

Most AI work right now is happening in the cloud with managed APIs and relatively clean data. Some of our customers cant do that: theyre operating in classified or regulated environments with filesystem metadata spanning billions of files. The AI problems here are genuinely hard the deployments are genuinely constrained and the work actually matters to science and research.

If you want AI work thats genuinely constrained genuinely consequential and cant phone home to OpenAI this is it.

Job Overview

Starfish manages petabytes of unstructured data for national labs research institutions fintech and pharma the kind of data that doesnt fit neatly into databases or cloud buckets. Were 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. Were tackling hard questions too: should an agent be permitted to move 2PB of data autonomously How do you govern that

In this role youll 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 isnt an option. Youll also support customers when things dont work: which means you need to actually understand what youve built.

Responsibilities and Duties include:

MCP & Agent Development

• Build and expand MCP servers that expose Starfishs 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

Customer-Facing Technical Work

• 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 doesnt have to figure it out from scratch

Benefits
We recognize that satisfaction and well-being are essential to long-term sustainability and business success. Full-time employees are eligible for the following benefits:

• Salary with potential for future commissions
• Multiple health insurance options
• Medical FSA and Dependent Care FSA
• Dental insurance
• Vision insurance
• 401(k) savings plan with employer matching
• Employer-sponsored long-term disability insurance
• Paid holidays and PTO (increasing with tenure)
• Discounted health club membership
• Many opportunities for growth

Equal Opportunity Employer
Starfish Storage provides equal employment opportunities (EEO) to all employees and applicants without regard to race color religion gender sexual orientation gender identity or expression national origin age disability genetic information marital status amnesty military service or veteran status in accordance with applicable federal state and local laws.

This position may require a background check.

Salary based on experience