Warehouse AI Orchestration Lead
Speak to KitOverview A growth-stage logistics technology company is hiring a Warehouse AI Orchestration Lead based in Chicago. This is a full-time, permanent role with a hybrid working pattern of 2 to 3 days per week in the office and up to 15% travel to customer sites. The salary is $120,000 to $155,000 per year, with benefits including stock options, flexible PTO, health insurance, and a 401(k). The business already has deep product capability on the transportation side, covering tendering, tracking, scheduling, documents and claims. The next frontier is extending that AI agent layer into warehouse operations, and this role owns that build. You will be the person who maps how WMS data and transactions connect to the dock, the yard, the TMS and the ERP, and who turns that knowledge into agent specs the product team can actually build. This is a new product, and the right person will help shape what it becomes. If you think in patterns rather than point solutions, and you'd rather build something repeatable once than configure it fifty times, this is the role for you. Key Responsibilities Map cross-system workflows from dock to stock and order to ship, showing where each event, object and decision lives across WMS, YMS, TMS and ERP Rank warehouse exception workflows by frequency, cost and automation potential, then decide which agents take on first Define what each agent senses, decides and does, what it may write back to the WMS, and where a human stays in the loop Work with engineering on how to read from and write to tier-1 WMS platforms via APIs, events, EDI, flat files and middleware Spend real time on distribution centre floors with design-partner customers, acting as the domain expert alongside engineers Help sales and solutions teams pitch and scope warehouse use cases credibly with VPs of distribution and their IT teams Requirements Must-haves 6 to 10 years across warehouse operations and WMS implementation, integration or solution consulting Hands-on experience with at least two of: Manhattan (WMOS or Active WM), Blue Yonder WMS, SAP EWM, Oracle WMS Cloud, Korber/HighJump, Infor WMS Fluency in the WMS object model: ASNs, receipts, LPNs, putaway, replenishment, waves, tasks, picking, load building, ship confirm Experience building or specifying WMS-TMS-ERP integrations (EDI 856/940/945, APIs, middleware), including where they break in production Real floor time in a distribution centre, as a supervisor, engineer, analyst or on go-lives Product instinct: builds repeatable patterns, not one-off configurations Comfort working closely with fast-moving engineering teams Nice-to-haves Experience with yard, dock scheduling or labour management systems Exposure to AI agents, LLM-based automation or orchestration platforms Pre-sales or solution consulting experience with enterprise shippers Spanish or Portuguese fluency What Success Looks Like Deep fingerprints on the AI agents roadmap by the end of year one, not just advisory input Warehouse exception workflows ranked, documented and translated into agent specs the product team can build from WMS integration patterns defined in a way that scales across customers, not customer by customer Trusted by both the product team and customers as the person who understands how warehouses actually run Team and Culture A product team that values domain depth and wants someone who can bridge warehouse reality and engineering execution A collaborative environment where the expectation is to sit with engineers as a domain expert, not to write tickets from a distance A company that moves fast and values people who can operate without a fully formed playbook Challenges Most discovery work happens remotely, so building the kind of floor-level intuition this role depends on requires deliberate effort without regular site access This is a new product, which means the roadmap is still taking shape - the right person helps define what gets built, rather than executing against a settled plan Prioritisation cal…