Forward Deployed Engineer

 

CommodityAI

Forward Deployed Engineer

Full-time Hybrid San Francisco, CA $150K - $250K

$150K–$250K base salary + competitive equity of 0.25%–0.75%

About this role

We are looking for a Forward Deployed Engineer with 3+ years of experience to own the end-to-end technical deployment of CommodityAI's product with customers — from sales handoff through stable production. You'll be the first FDE hire at a YC- backed AI startup growing 3x in 6 months, acting as the technical PM, onboarding lead, and customer champion all in one.

What will you be doing?

Own the full customer onboarding lifecycle — taking customers from sales handoff to live production within the first weeks of a 3-month paid pilot

Act as the technical PM for each customer: bridging engineering and customer stakeholders, managing timelines, and keeping deployments unblocked

Configure and tune AI agents and automation workflows to fit each customer's operational data and logic

Build internal and external tooling to help future FDEs and customers onboard faster and more independently

Lead customer calls (kickoffs, progress updates, training) across SMB, mid-market, and enterprise accounts — with up to 30% travel for enterprise customers globally

Key Requirements

Prior experience in a customer-facing engineering or technical deployment role (FDE, Solutions Engineer, Implementation Engineer) — ideally at an early-stage startup where you owned both the technical and project management sides

Strong project management skills with demonstrated ability to juggle multiple concurrent customer deployments without dropping balls

Deeply embedded in AI tools and agents in your day-to-day — you should be actively automating your own workflows, not just aware of the space

Technically credible: able to read, write, and troubleshoot basic Python or TypeScript code and understand APIs and data flows

 

 

Based in San Francisco and able to work in-office 4 days/week; willing to travel globally (up to 30%) for enterprise customer visits

3 - 7 years of experience

in a generalist IC customer-facing technical deployment role (FDE, Solutions Engineer, or Implementation Engineer)

Salary

$150K - $250K ($150K–$250K base salary + competitive equity of 0.25%–0.75%)

Equity

0.25-0.75%

Visa sponsorship not available

Hybrid work policy

4 days in-office in San Francisco, CA

Full-time position

Location

San Francisco, CA

Report to

https://www.linkedin.com/in/dcervoni/

Tech stack

Python, TypeScript, LLMs / AI Agents

About CommodityAI

CommodityAI is a 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. Whether it's automating deal capture, shipment reconciliation, or invoice review, CommodityAI helps teams work with greater clarity, precision, and far less manual effort.Based in San Francisco, CommodityAI was founded by former commodity traders and operators with deep industry expertise. Backed by leading investors including Y Combinator and Rebel Fund, we’re building intelligence at the foundation of global trade.

 

 

Team size

6 employees Founded

2024

Website

www.commodityai.io LinkedIn

Visit

Total funding

$2M+ Company locations

San Francisco, California

About the team

CommodityAI is a small, high-ownership team of fewer than 10 people — and everyone on it is genuinely exceptional at something. The culture is built around deep domain expertise, strong individual agency, and a shared belief that the most important work happens in industries that aren't glamorous but matter enormously.

The founding team brings rare operator credibility. Philip, the CEO, spent 10 years as a sugar trader — he's not guessing at customer pain, he's lived it. Daniel, who leads forward deployment, built AI hardware and software for logistics companies at Samsara. CTO Kyle comes from construction software, and founding engineer Zach is a former YC founder and staff engineer from Flexport. The team isn't a group of generalist technologists who stumbled into commodities — they're operators and engineers who understand the physical world of trade from the inside.

This is a high-agency, low-handholding environment. Everyone operates with a lot of ownership. Daniel is explicit about this: the team is seasoned and staff-level, and the expectation is that you take initiative, figure things out, and move fast — not wait to be told what to do. If you need a lot of structure to get going, this probably isn't the right fit.

The culture rewards curiosity and initiative over credentials. Education and pedigree don't matter here. What does matter is whether you're genuinely interested in the problem, whether you're staying on top of AI and applying it in your own work, and whether you have the hunger to build something from scratch. Side projects, self- directed learning, and a founder mentality are all signals the team actively looks for.

They're building fast — and they know it. CommodityAI just crossed $2M ARR with 3x growth in 6 months, and the sales pipeline is outpacing the team's ability to build

 

 

and onboard. The people joining now are shaping how the company scales, not inheriting a playbook someone else wrote.

If you're energized by working on hard operational problems with a tight team of people who are genuinely great at what they do — and you're not looking for a hyped brand name on your resume — this is the kind of place where you can do some of the best work of your career.

Tech stack

Python, TypeScript, LLMs / AI Agents

The product

CommodityAI is a purpose-built AI platform for the commodities industry — automating the document-heavy, operationally complex workflows that define physical commodity trading.

At the core of the product is an AI Workspace that acts as a digital operator for commodity businesses. It continuously interprets unstructured data from emails, PDFs, and legacy systems, reconciles it against systems of record, and flags issues in real time. Key workflows it automates include:

• Deal capture — extracting and structuring trade data from incoming correspondence and documents

• Shipment reconciliation — matching logistics data across counterparties and flagging discrepancies

• Invoice review — processing and validating financial documents with precision

• Post-trade execution — managing the operational tasks that follow a completed trade across dozens of counterparties

For any given commodity transaction, there may be tens of thousands of documents and email threads involving dozens of counterparties. CommodityAI's AI agents absorb that complexity, giving trading, logistics, finance, and compliance teams greater clarity and far less manual effort.

The platform is designed for the companies moving the natural resources that feed the world, build cities, and power everything in between — from sugar mills in Guatemala to end consumers like Nestlé and Coca-Cola.

 

 

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