Forward Deployed Engineer

Nav Logic AI was founded by veterans of the supply chain and logistics industry who have spent decades navigating the complexity of global freight, warehouse operations, last-mile delivery, and demand planning. Frustrated by legacy software that lagged years behind real-world challenges, our founders set out to build the AI-native platform the industry actually deserves.

We sit at the intersection of deep operational expertise and cutting‑edge AI — applying large language models, computer vision, and predictive analytics to the messy, high‑stakes world of physical goods movement. Our customers range from regional carriers to Fortune 500 manufacturers, all looking for intelligence that works as hard as they do.

We are looking for a Forward Deployed Engineer who can sit on a Class‑8 trailer dock in the morning, refactor a Python data pipeline by lunch, and present a Pareto chart of throughput gains to a VP of Operations by EOD. This is the role for engineers who believe software is only valuable when it changes what happens on the floor.

You will be the first Nav Logic AI engineer a customer meets after they sign — embedded with their team, instrumenting their data, and turning our platform into a measurable result on their P&L. You partner closely with Product and AI Engineering to feed real‑world friction back into the roadmap. If you’ve ever delivered a Palantir‑style deployment, run a Series A solutions‑engineering team, or shipped customer‑facing tooling at a logistics tech company, you’ll feel at home here.

• Customer Deployment Ownership Lead end-to-end deployments at carriers, 3PLs, and Fortune 500 manufacturers — from kickoff through go‑live and value realization. You own the technical outcome.
• Data & Systems Integration Build connectors and pipelines into customer TMS, WMS, ERP, and EDI/API endpoints (SAP, Oracle, Manhattan, Blue Yonder, Project
  44, Mercury Gate, Net Suite). Make messy data usable.
• Custom Solution Engineering Configure and extend the Nav Logic platform to fit each customer’s ops — building dashboards, workflows, and AI‑assisted tooling on top of our SDK and APIs.
• On‑Site Operational Discovery Spend time in the warehouse, the dispatch room, and the dock — observe workflows, time motion, and translate operational pain into engineering specs.
• Production Reliability Instrument deployments with monitoring, on‑call rotations, and incident response. When a model regresses or a feed stalls at 3 a.m. PT, you’re the first responder.
• Roadmap Feedback Loop Be the highest‑bandwidth signal Product and AI Engineering have into customer reality. Convert what you learn into structured PRs, RFCs, and roadmap inputs — not just Slack venting.
• Reusable Accelerators Productize the patterns you encounter twice. Build templates, reference architectures, and internal libraries so the next deployment is faster than the last.
• Customer Trust & Storytelling Present technical work to customer execs in plain language; partner with PMM and Sales on case studies, ROI models, and reference calls.

• 5+ years building software in production — at least 2 of those in a customer‑facing or forward‑deployed role (FDE, Solutions Engineer, Implementation Engineer, or similar).
• Strong engineering fluency in Python and Type Script ; comfortable in SQL and at least one cloud (AWS, GCP, or Azure).
• Track record of shipping integrations against enterprise systems — REST/GraphQL APIs, EDI, SFTP feeds, message queues, and the gnarly edge cases each of those produces.
• Demonstrated ability to be the technical owner in a customer room : scoping, estimating, escalating, and delivering — without a PM holding your hand.
• AI‑native mindset : you use…