Location: San Francisco, CA
Work policy: Hybrid — four days per week in office
Employment: Full-time
Salary: $165,000–$240,000
Equity: 0.1%–0.3%
Travel: Up to 30%, including international travel
About CommodityAI
CommodityAI is purpose-built AI for the commodities industry—where the physical world meets intelligence.
Our AI Workspace automates document-heavy workflows across trading, logistics, finance, and compliance. From deal capture and shipment reconciliation to invoice review, CommodityAI helps teams operate with greater clarity, precision, and far less manual effort.
Founded by former commodity traders and operators, CommodityAI is backed by Y Combinator and Rebel Fund. We have surpassed $2 million in ARR, grown 3x in six months, and signed major enterprise customers, including Cargill.
The Opportunity
We are hiring an AI Forward Deployed Strategist to own end-to-end customer deployments, transforming messy, real-world commodity trading workflows into production AI systems.
You will be one of our first forward-deployed hires and one of the company’s first ten employees. You will work directly with customers, engineering, and product while helping build our deployment function from the ground up.
This is a hands-on individual-contributor role for someone who combines structured problem-solving, customer leadership, operational judgment, and genuine fluency with modern AI tools.
What You’ll Do
Own the complete deployment lifecycle across multiple customers, including discovery, scoping, configuration, user acceptance testing, launch, and go-live.
Map customer workflows and operational pain points to CommodityAI’s AI agent platform.
Define data models, field mappings, business rules, agentic steps, deterministic logic, and human-review requirements.
Lead kickoffs, working sessions, training, and UAT with stakeholders ranging from warehouse operators to VP- and director-level executives.
Act as the internal project manager for each customer, maintaining momentum, surfacing risks, and driving ambiguous problems toward concrete outcomes.
Translate deployment learnings into structured product feedback for engineering and product.
Build implementation playbooks, templates, runbooks, and internal tools that help future deployments move faster.
Use AI-assisted development tools such as Claude, Codex, and Cursor to prototype solutions and automate workflows.
Travel to customer sites when necessary, including locations across the United States, Europe, and Asia.
What We’re Looking For
Approximately 1–5 years of experience in deployment, implementation, consulting, business operations, strategy and operations, or a related customer-facing role.
Demonstrated ownership of complex implementations from discovery through go-live.
Strong project-management skills and the ability to manage several parallel deployments without losing momentum or detail.
Genuine daily fluency with AI tools such as Claude, Codex, Cursor, or similar platforms.
Evidence that you have personally built, automated, or prototyped workflows with AI—not solely used AI for writing and summarization.
Comfort working with structured data, including CSV, JSON, field mappings, APIs, and basic data models.
Ability to troubleshoot workflows and reason about systems without depending on engineering for every issue.
Clear communication across technical and nontechnical audiences, from frontline operators to executives.
Comfort operating in an early-stage environment and remaining deeply hands-on as an individual contributor.
Based in San Francisco or willing to relocate, with the ability to work from our office four days per week.
Willingness to travel up to 30%, including internationally.
Relevant Backgrounds
Strong candidates may come from several paths, including:
Strategy consulting—particularly MBB—with subsequent hands-on startup experience.
Business operations or strategy and operations at an early-stage company.
Applied-AI deployment, solutions, implementation, or professional-services roles.
Experience deploying AI agents or workflow-automation products in enterprise environments.
Implementation roles where you personally owned discovery, configuration, UAT, and launch.
Experience in commodities, logistics, supply chain, energy, trade finance, or another operationally complex industry is helpful but not required.
Our Technology Environment
AI agents and agentic workflows, Claude and Anthropic, Codex, structured data, JSON, CSV, APIs and system integrations, data modeling, SQL, Python, TypeScript, AI-assisted development tools, and ERP, ETRM, and CRM systems.
Why Join CommodityAI
Real traction: We have crossed $2 million in ARR and grown 3x in six months, with more customer demand than the current team can onboard.
A problem worth solving: Our founders spent years inside commodity trading and experienced these operational problems firsthand.
Meaningful ownership: As one of our first ten employees, you will directly shape our deployment methodology, tooling, and team.
Compelling upside: Competitive cash compensation and meaningful early-stage equity in a company already serving enterprise customers.
High-impact work: You will turn complex physical-world operations into production AI systems for one of the world’s largest and most underserved industries.