Staff AI Platform Engineer

Are you ready to build America’s energy future? Form Energy is an American manufacturing and energy technology company. We’re revolutionizing energy storage with cost-effective, multi-day technology designed to keep the electric grid secure and reliable, even during extended periods of stress. By strengthening the electric system and reimagining what’s possible, we’re giving clean energy a whole new form!

In recent years, Form Energy has earned a number of accolades, including being named by TIME as a “Best Invention”, MIT Technology Review as a “Top Climate Tech Company To Watch”, and Fast Company as “One of the Next Big Things In Tech”. We are making rapid progress on our mission of delivering energy storage for a better world, and our team is growing just as rapidly to meet demand. We have signed contracts with leading electric utilities across the United States and production of our iron-air batteries is underway at our first high-volume manufacturing facility in West Virginia.

Working for Form Energy is more than just a job, it’s a chance to be part of something extraordinary. And now - right as we significantly scale up battery manufacturing -  might be the most exciting moment in the company’s history to join. We are assembling a team of highly talented and driven individuals across the country. Driven by our core values of humanity, excellence, and creativity, our team is determined to deliver on our mission and transform the energy landscape for the better.

Feeling energized to make a meaningful impact on the world? Then keep reading - you’ve come to the right place.

ROLE DESCRIPTION

Form Energy is hiring a Staff AI Platform Engineer to build the shared platform that lets people across the company build and run AI-powered tools safely and quickly. As a hands-on senior individual contributor, you will help design the application runtime, knowledge systems, agent infrastructure, and governance tooling that teams would otherwise build separately, and you will help set the patterns other engineers follow. Your work spans product R&D, design, manufacturing process engineering, product costing, and root cause analysis. It draws on data from our battery test stands, factory manufacturing robots, and deployed projects in the field, along with the documents, slide decks, transcripts, and conversations our teams produce every day. You will sit on the AI & Data Platform team, working with data engineers, software engineers, Information Security, and the scientists, engineers, and operators who use what you build. This is an exciting opportunity to shape how a fast-moving company with breakthrough technology and an incredible mission puts AI to work.

This is a hybrid role, which will require working onsite from our office in Berkeley, CA, Somerville, MA or Weirton, WV 3+ days per week.

Relocation assistance is available.

WHAT YOU'LL DO:

• Build and operate the internal application platform that lets employees create and deploy AI-generated applications on curated backend and frontend frameworks, with starter templates, design guidance, authentication, and secure deployment built in, so app authors own only business logic, user flows, and UI.

• Give those applications governed access to data, including connectivity to our data warehouse and a shared Postgres cluster for application state that is automatically integrated into our data platform.

• Build and operate a central knowledge platform over unstructured content (documents, slide decks, meeting transcripts, Slack) and structured data from battery test stands, manufacturing robots, and deployed systems, pairing document retrieval with query access to structured data through semantic models and text-to-SQL. Own its retrieval quality through semantic and hybrid search, re-ranking, chunking, and classification, with source-level permissions and evaluation sets that show whether a change helps.

• Design and deploy the shared MCP infrastructure, including a gateway layer (such as agentgateway) for authentication, authorization, rate limiting, and audit logging, and build MCP servers for applications and services across the software org and for selected external tools.

• Own model selection and cost: evaluate open-source and open-weight models against frontier models on our own tasks, decide where each fits, and reduce token usage through context management, caching, and model routing.

• Build the agent orchestration layer, including multi-agent workflows and long-running loops with checkpoints, human review gates, and automated evaluation. Work with data engineers to decide when work should run as a deterministic, scheduled workflow and when it needs a graph or state machine in which an agent chooses among bounded steps.

• Partner with product R&D, battery design, manufacturing process engineering, product costing, and root cause analysis teams to find repeatable work and automate it, including agent workflows whose output informs critical design and process decisions.

• Instrument the platform with tracing, evaluation, and usage and cost attribution by team, and stand up the AWS infrastructure and infrastructure-as-code (Pulumi and/or Terraform) it runs on.

• Help stand up a company-wide skills and plugin marketplace that vets contributions against AI policy and scans them for security vulnerabilities with open-source and commercial tools. Advise on AI governance, recommending changes that make the policy specific to platform needs and automating its execution, such as approvals for new tools.

• Raise the engineering bar through design docs and RFCs, code review, mentorship, and technical influence that reaches beyond the immediate team.

WHAT YOU'LL BRING:

• Bachelor's degree in computer science, software engineering, computer engineering, or a related field plus 7+ years of software or data engineering experience, including building and operating production platforms or services that other engineers depend on.

• Strong production programming in Python and Go, with experience building APIs and backend services.

• Hands-on experience building LLM-powered systems in production, including retrieval-augmented generation, embeddings, vector and hybrid search, re-ranking, and structured-data access through text-to-SQL or semantic layers.

• Experience with agent frameworks, tool calling, and the Model Context Protocol, and with workflow orchestration or state-machine frameworks such as LangGraph, Temporal, or Dagster.

• Experience building evaluation sets and harnesses for LLM systems and measuring quality, latency, and cost across model providers, including open-weight models.

• Experience with PostgreSQL and a cloud data warehouse, plus AWS, containers, CI/CD, and infrastructure-as-code with Pulumi and/or Terraform.

• Working knowledge of platform and AI security: authentication and authorization (OAuth/OIDC), secrets management, sandboxed execution, tenant isolation, supply-chain scanning, and risks specific to LLM tools such as prompt injection and data exfiltration.

• A track record of building internal platforms that other teams adopt, and of independently leading the design of novel solutions through technical design docs and RFCs.

• Excellent communication and organizational skills, including with scientists, engineers, and operators who aren't software developers, and comfort participating in an on-call rotation.

• Nice to have: React and design-system experience; Snowflake or Databricks; serving open-weight models (for example with vLLM); API or AI gateway experience; AI governance or compliance frameworks (SOC 2, ISO 27001); background in battery, energy, manufacturing, or other physical-systems data.

#LI-Hybrid

Humanity is a cornerstone of Form Energy’s culture, and we make sure our compensation and benefits reflect that. Form Energy offers competitive salaries, stock options, and a holistic benefits package to ensure all employees have what they need to thrive while