Forward Deployed Engineer - Supply Chain Solutions

Posted: 2026-08-05

- Embed & Map: Travel to client sites to map end-to-end supply chain processes, audit legacy systems, uncover hidden financial leaks, and translate complex operational constraints into technical architectures.

- Design and build production solutions spanning customer applications, internal tools, APIs, data pipelines, decision-support systems, and workflow automations connecting directly to client ERPs (SAP, Oracle, NetSuite), WMS, and TMS systems

- Build & Deploy Applied AI Solutions: Design and ship production-grade AI applications, agentic LLM workflows, and decision engines.

- Solve Complex Mathematical Optimization: Apply optimization algorithms and analytical methods to real-world logistics challenges to problems such as routing, mode selection, inventory positioning, container utilization, consolidation, and exception prioritization.

- Own the 90-Day Sprint Lifecycle: Drive high-velocity deployment sprints, taking solutions from discovery and architecture to live production deployment, operator adoption, and verified hard-dollar ROI measurement.

- Productize the Field: Partner closely with Flexport core Product and Platform Engineering teams to turn custom, field-tested client builds into reusable platform capabilities for our global logistics engine.

- Bridge Engineering & Operations: Work side-by-side with frontline logistics teams at ports, cross-docks, and client sites to validate code in live operational workflows, train users, and ensure lasting adoption.

- Drive Executive Decisions: Communicate technical trade-offs, system architecture, and financial outcomes directly to client technical leaders and C-suite executives.

You Should Have

- Educational Background: BA/BS degree or equivalent practical experience in Computer Science, Software Engineering, Operations Research, Applied Mathematics, or a related technical field.

- Full-Stack Production Engineering: 4+ years of professional software engineering experience building customer-facing or mission-critical applications (Python, TypeScript/React, SQL, REST/GraphQL APIs, relational databases, and event-driven architectures).

- Hands-on AI & Systems Experience: Demonstrated ability to build and integrate AI/ML solutions (LLM orchestration, agentic workflows, machine learning models, or mathematical optimization solvers).