Forward Deployed Engineer

CommodityAISan Francisco, CA
Onsite

About The Position

CommodityAI is building the operating system for the global commodities industry, the foundational sector responsible for moving the world's energy, metals, and agricultural resources. Today, our platform actively manages billions of dollars of commercial contracts. Behind every physical trade and shipment lies an incredibly complex layer of manual operations, with critical data trapped in unstructured emails, PDFs, and legacy software. CommodityAI serves as a digital operator that continuously interprets trade data, reconciles physical movements, and flags operational risks in real time. We are a Y Combinator-backed company (W24) supported by top-tier investors, including Rebel Fund and the founders of YouTube and Reddit. We are currently building our forward deployed team in San Francisco to onboard customers faster, translate real-world operations into working software, and turn one-off implementations into product.

Requirements

  • 3+ years in forward deployed, solutions, implementation, or customer-facing product engineering, ideally at an early-stage company.
  • Deeply embedded in AI tooling: You are actively automating and building with agents in your own work, not simply aware of the space.
  • Practical coding bar: You read, write, and debug Python or TypeScript, and you are fluent with APIs, structured data, and system dependencies.
  • Parallel execution: You run several concurrent deployments without dropping details.
  • End-to-end ownership: You have carried at least one deployment from onboarding through implementation, go-live, and stabilization.
  • Range as a communicator: You can hold a working session with a nontechnical operator in the morning and a customer IT team in the afternoon.

Nice To Haves

  • Commodities, logistics, energy, or another operationally complex industry
  • production LLM and extraction pipelines
  • integrations with ERP, ETRM, or CRM systems of record

Responsibilities

  • Own Deployments End to End: Take customers live during the opening weeks of a paid pilot, owning success criteria, UAT, go-live, and production stability.
  • Work Onsite With Customers: Run kickoffs, training sessions, and working sessions at customer offices across the US, Europe, and Asia, where being in the room is what unblocks a deployment.
  • Translate Messy Operations: Run discovery across trading, logistics, finance, and compliance, then turn ambiguous workflows into data models, business rules, integrations, and human approval steps.
  • Deploy Production AI/LLM Workflows: Configure, evaluate, and tune agents against real customer data, deciding where an agent belongs, where deterministic logic is safer, and where a human has to review.
  • Execute Hands-On: Write and troubleshoot practical Python and TypeScript, and inspect APIs, payloads, logs, and document outputs to diagnose issues in production.
  • Build the Function: Create the tooling, templates, and playbooks that let the FDE team we build behind you deploy faster, and feed recurring customer needs back into the core product.

Benefits

  • Competitive base salary with meaningful early-stage equity.
  • Comprehensive health, dental, and vision insurance.
  • A high-trust, low-bureaucracy environment where you have a direct seat at the table.
  • Direct collaboration with the founding team and an agile, elite technical team.
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