RELEX Solutions

RELEX Solutions

Forward Deployed Engineer

Atlanta, GA, United States · Staff+

Work authorization requiredDetected 28 days ago
TypeScriptReactGCPCloud PlatformsMachine LearningData EngineeringDesign SystemsForecastingSupply ChainDemand Planning

About the role

  • What we need you to do This is not a consulting role or a solutions architect role.
  • Engage across the full customer organization: from C-suite to shop floor.

Responsibilities

  • You own relationships at every level, from the executive sponsor setting the mandate to the store staff running your solution day to day
  • Comfortable using AI in your everyday work and developing AI tool adoption as an organizational strategy

Requirements

  • Strong understanding of data modeling, observability, and hypothesis-driven development
  • Solid working knowledge of cloud platforms, and modern data stacks

Skills

  • What we need you to do
  • The goal is to make integrations as seamless as possible.
  • production-grade data pipelines and integrations that handle large-scale, customer-specific datasets in cloud environments

Benefits

  • Practical benefits supporting work, family, wellness, and everyday life

Company info

  • 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.
  • With a global team of over 2,000 professionals, we work side-by-side with our customers to solve real problems with lasting impact.
  • Companies trust RELEX to increase product availability, boost sales, deliver actionable insights, improve sustainability, and drive profitable growth.
  • Within RELEX, our Pricing & Promotions team builds cloud-native tools on Google Cloud Platform (GCP) that help businesses make smarter pricing decisions.
  • From large-scale data processing pipelines in Go to intuitive TypeScript/React user interfaces, we design systems that are fast, scalable, and meaningful.
  • In response to our fast growth and market expansion, we are looking for a Forward Deployed Engineer to join our Pricing & Promotions team.
  • This is not a consulting role or a solutions architect role.
  • You will write production code that runs in live customer environments, own data pipeline deployments end to end, and be the technical face of RELEX Pricing & Promotions to US retailers.
  • The role could be thought of as a mix of traditional data/platform/sw engineering, with the addition of developing very closely with the customers.
  • That means that you will vibecode prototypes with the customers and then implement those into the product.
  • Lead requirements end to end: gather, understand, workshop, challenge, and agree on what customers actually need, not just what they ask for.
  • You make sure we build the right thing
  • Design and ship: production-grade data pipelines and integrations that handle large-scale, customer-specific datasets in cloud environments
  • Own outcomes: KPI delivery, solution performance, and SLAs.
  • You know what "works" means in measurable terms, and you stay accountable until you get there
  • What you'll bring to the table
  • Proven experience designing and building scalable data pipelines for large-scale data processing, in production, not just in dev
  • Experience building integrations for downstream or customer-facing systems
  • 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
  • Fluent in written and spoken English
  • What we consider an advantage

Visa & Work Authorization

  • You own relationships at every level, from the executive sponsor setting the mandate to the store staff running your solution day to day

This listing is sourced directly from RELEX Solutions's careers page and normalized into a canonical job model.