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Form Energy

Iron-air multi-day energy storage systems

Staff AI Platform Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • A bachelor's degree in computer science, software engineering, computer engineering, or a related field, plus 7 or more years of software or data engineering experience, including building and operating production platforms or services that other engineers depend on.
  • Strong production programming skills in Python and Go, with experience building application programming interfaces and backend services.
  • Hands-on experience building production large language model-powered systems, 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, the Model Context Protocol, and workflow orchestration or state-machine frameworks such as LangGraph, Temporal, or Dagster.
  • Experience building evaluation sets and harnesses for large language model systems and measuring quality, latency, and cost across model providers, including open-weight models.
  • Experience with PostgreSQL, a cloud data warehouse, AWS, containers, continuous integration and continuous delivery, and infrastructure-as-code using Pulumi and/or Terraform.
  • Working knowledge of platform and AI security, including authentication and authorization (OAuth/OIDC), secrets management, sandboxed execution, tenant isolation, supply-chain scanning, and risks specific to large language model tools such as prompt injection and data exfiltration.
  • A track record of building internal platforms adopted by other teams, and independently leading the design of novel solutions through technical design documents and RFCs.
  • Communication and organizational skills to work with scientists, engineers, and operators who are not software developers, and comfort participating in an on-call rotation.

Responsibilities

  • Build and operate the internal application platform that enables employees to create and deploy AI-generated applications on curated backend and frontend frameworks, with starter templates, design guidance, authentication, and secure deployment, so application authors own only business logic, user flows, and user interface.
  • Give applications governed data access, including connectivity to the data warehouse and a shared PostgreSQL cluster for application state that is automatically integrated into the data platform.
  • Build and operate a central knowledge platform over unstructured content such as documents, slide decks, meeting transcripts, and Slack, and structured data from battery test stands, manufacturing robots, and deployed systems. Pair document retrieval with structured-data query access through semantic models and text-to-SQL. Own retrieval quality through semantic and hybrid search, re-ranking, chunking, and classification, with source-level permissions and evaluation sets that measure whether changes help.
  • Design and deploy shared Model Context Protocol infrastructure, including a gateway layer such as agentgateway for authentication, authorization, rate limiting, and audit logging, and build Model Context Protocol servers for applications and services across the software organization and selected external tools.
  • Own model selection and cost by evaluating open-source and open-weight models against frontier models on company tasks, deciding where each fits, and reducing 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 determine 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 research and development, battery design, manufacturing process engineering, product costing, and root cause analysis teams to identify repeatable work and automate it, including agent workflows whose outputs inform critical design and process decisions.
  • Instrument the platform with tracing, evaluation, and usage and cost attribution by team, and establish the AWS infrastructure and infrastructure-as-code (Pulumi and/or Terraform) on which it runs.
  • Help establish a company-wide skills and plugin marketplace that vets contributions against AI policy and scans them for security vulnerabilities using open-source and commercial tools. Advise on AI governance by recommending policy changes specific to platform needs and automating execution, such as approvals for new tools.
  • Raise the engineering bar through design documents and RFCs, code review, mentorship, and technical influence beyond the immediate team.

Desired Qualifications

  • React and design-system experience.
  • Snowflake or Databricks experience.
  • Experience serving open-weight models, for example with vLLM.
  • API or AI gateway experience.
  • AI governance or compliance framework experience, such as SOC 2 or ISO 27001.
  • Background in battery, energy, manufacturing, or other physical-systems data.

About the Company

Form Energy

Iron-air multi-day energy storage systems

Form Energy develops and sells energy storage systems designed for long-duration use in the electric grid. Its main product is an iron-air battery that can store electricity for up to about 100 hours, offering a cost-effective alternative to traditional power plants and enabling a fully renewable grid. The system works by storing energy chemically in iron and air, allowing electricity to be released when needed over multi-day stretches, with a focus on scalable manufacturing and system integration to meet utility and municipal needs. The company differentiates itself by pursuing low-cost, multi-day storage on a large scale, leveraging iron as a plentiful material to deliver affordable, reliable energy storage compared to conventional approaches. Its goal is to support deep decarbonization of the electric system by providing reliable, year-round renewable power through affordable energy storage and deployment alongside grid infrastructure.

Company size
501-1,000
Company stage
Debt Financing
Total funding
$2.6B
Headquarters
Somerville, MA
Founded
2017

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