Forward Deployed Engineer, Data & Integrations

About Us

We’re ClosedWon Talent, a sales and go-to-market recruiting agency that specializes in working with fast-growing startups. If you’re exploring your next move, we might have just the opportunity for you, including this one.

About the Company

Most companies still plan their supply chains, meaning quantities, mix, allocations, and timing, in spreadsheets or legacy software. The spreadsheets break as soon as the business moves quickly. The legacy suites take a year to implement and frequently lose to the spreadsheets anyway.

Atomic is rebuilding the brain behind the American supply chain. By tackling operations optimization from first principles with an AI-native stack, they deliver unprecedented results at breakneck speed for their customers. Customers include DoorDash, HelloFresh, Archer Meat Snacks, Starface World, LMNT, OOFOS, Cora, and Chomps.

The founders lived this problem before they built the solution. Michael Rossiter and Neal Suidan built Tesla’s end-to-end supply chain orchestration system from scratch during the Model 3 ramp, after watching a company that size run on spreadsheets that could not keep up with how fast the business moved. Revenue has grown roughly 10x this year.

About the Role

Every Atomic deployment starts with a customer’s data, and that data arrives however it happens to exist: an ERP export, a WMS feed, a partner API, an emailed spreadsheet, a file someone has been maintaining by hand for six years. Nothing moves until it’s wired in, normalized, and trustworthy.

This role owns that layer across the customer base. Where the standard Forward Deployed Engineer goes deep on one complex engagement at a time, you’d go broad — running integrations and pipelines for several customers in parallel, applying playbooks where they exist and improving them where they don’t.

It’s still a customer-facing job. You’d be on calls with the customer’s technical teams working out what their systems actually contain, explaining what’s feasible, and telling them directly when something is broken on their end or when a timeline is slipping. The engineering team builds and maintains the platform foundation; you connect each customer to it and make the data underneath it reliable.

The hard part isn’t the code. Customers hand you data in every format and state of cleanliness, tell you what they think they need, and some of it will be wrong. Figuring out what to actually build, and building it fast, is what you'll be doing.

What You’ll Do

• Build automated, normalized pipelines on top of a customer’s messy real-world supply chain data
• Wire Atomic into customer systems, ERPs, WMSs, partner platforms, and whatever else the data lives in
• Own integrations end to end, from scoping with the customer’s technical team through production and ongoing reliability
• Run several customer projects at once and keep quality consistent across all of them
• Work directly with customers on technical conversations, including the uncomfortable ones about bad data and delays
• Use AI tooling to compress delivery time, and help improve how the team works with customer data rather than just repeating existing practice

Must-Have Requirements

• 3+ years of data engineering, integrations, or pipeline work, with real ownership rather than tickets
• Strong, current Python skills
• Daily working fluency with Claude and modern AI coding tools
• Hands-on integration experience across systems like ERPs, CRMs, WMSs, APIs, file drops, and email-based feeds
• A track record of running multiple technical projects at once without quality slipping
• Comfort sitting in front of customers and owning the technical relationship, including explaining problems and setbacks directly
• The ability to take thin, messy, incomplete context and still deliver an excellent outcome quickly
• Ability to work autonomously without heavy direction
• Based in NYC area

Nice to Have

• Supply chain, planning, or physical goods exposure
• Experience at an early-stage startup, or a clear reason you want one now