Forward Deployed Engineer | Merchandising
Listed on 2026-08-23
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IT/Tech
AI Engineer (Applied/Software), Data Analyst, Data Engineering
What We Do
RELEX Solutions delivers a unified supply chain planning platform for retailers and manufacturers, enabled by proven AI technology. We help companies optimize demand forecasting, replenishment, merchandising, pricing and promotions, supply chain operations, and production planning across the end-to-end value chain.
What We DoRELEX Solutions delivers a unified supply chain planning platform for retailers and manufacturers, enabled by proven AI technology. We help companies optimize demand forecasting, replenishment, merchandising, pricing and promotions, supply chain operations, and production planning across the end-to-end value chain.
Who We AreWe work on the decisions where retail margins are won and lost. Changing a price is easy. Knowing which of fifty thousand prices to change, what it does to demand, and whether last week’s promotion actually made money is not. That is what we build for. RELEX Solutions delivers a unified supply chain and retail planning platform for retailers and manufacturers, enabled by proven AI technology, with a global team of over 2,000 professionals working side-by-side with our customers.
Therole
In response to our fast growth in North America, we are hiring a Forward Deployed Engineer with a strong data science foundation for our US Merchandising business. You will be part of the central engineering team, and work with the US operations team, directly with US customers. You will be the scientific and technical face of RELEX Merchandising to US retailers.
WhatMakes This Role Different
This is not a consulting role and not a solutions architect role. You write production code and build production models that run in live customer environments. And it is not a generalist engineering seat: co-developing forecast and optimization improvements with a customer is science work, and the bar is set by some of the most demanding retailers in the US. The hard part of this job is not prototyping quickly.
The hard part is that the improvement you co-develop has to be right, hold up in front of the customer's own analysts, and then run in production every week. You walk in with a hypothesis, test it on their data, and stand behind the result, limitations included.
- Own technical delivery end to end, from discovery through go-live: configuration, extensions, integrations, and the quality of everything that ships into the customer's instance
- Prove the value you deliver by instrumenting deployments, measuring outcomes against the customer's baseline, and presenting the evidence credibly to operational users and executives alike
- Own the technical customer relationship, learning their operations deeply enough to challenge requirements and become their first call when a new problem appears
- Feed the product by capturing gaps and use cases from the field and prototyping solutions that can graduate into the RELEX roadmap
- Build customer self-sufficiency through knowledge transfer and clean handovers, so they can operate and extend RELEX without you
- Grow the account by surfacing adjacent use cases, new sites and unused capabilities, and shaping the technical solution and value case together with pre-sales and the account team
- Support commercial activity with feasibility assessments, proofs of concept and technical demos, so what gets agreed is technically grounded
- Proven experience designing and building scalable data pipelines for large-scale data processing in production
- Strong understanding of data modeling, observability, and hypothesis-driven development
- Experience building integrations for downstream or customer-facing systems
- Solid working knowledge of cloud platforms, and modern data stacks
- Strong business acumen: you can translate technical work into measurable financial impact and communicate it clearly to a non-technical audience
- Comfortable managing ambiguity and taking full ownership of outcomes
- Willingness to travel and to work on-site at customer locations for parts of an engagement
- Comfortable using AI in your everyday work and developing AI tool adoption as an organizational strategy
Nice to have: exposure to retail, merchandising,…
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