AI Led Forward Deployed Engineer | Design & Digital Products

Accenture Plc

  • St. Louis, MO
  • 1 day ago

    Highlights

    Move from insight and concept through design, prototype, and production the way Design & Digital Products builds, connecting strategy directly to what ships. Design and build AI systems end to end: RAG architecture, agentic orchestration, prompt & context engineering, evals & guardrails, tool-use patterns, and MCP integration.

    Numbers & Facts

    LocationSt. Louis, MO

    Description

    You are:

    As an AI led FDE , you embed with design & product teams to originate, design, and ship AI-powered digital products and experiences into production. You will build on top of enterprise data and technology foundations to create AI-powered products that face customers, employees, and business users, driving revenue, engagement, and better decisions

    The work:

    • Identify where AI creates measurable business value before a brief exists. Originate use cases, prioritize by impact, and shape the engagement.
    • Differentiate through a product-led approach. Pair AI & data depth with product strategy and product thinking, so the work ladders to a real product and its outcomes, not a proof of concept.
    • Bring fluency in the design-to-product pipeline. Move from insight and concept through design, prototype, and production the way Design & Digital Products builds, connecting strategy directly to what ships.
    • Design and build AI systems end to end: RAG architecture, agentic orchestration, prompt & context engineering, evals & guardrails, tool-use patterns, and MCP integration.
    • Select the right model and approach: frontier-model selection, and when to apply fine-tuning (LoRA / PEFT) vs. prompt engineering vs. RAG, exercising judgment over execution across cost, latency, accuracy, and compliance tradeoffs.
    • Activate AI within the client's existing enterprise data platforms. Connect AI products to where the data lives using data-gravity patterns rather than re-architecting infrastructure.
    • Build AI-powered digital products and experiences full-stack, with production accountability. Ship working code, not recommendations.
    • Deploy responsibly to production: MLOps, model serving, security, and cost / latency discipline at product level, with effective monitoring.
    • Codify best-practice delivery patterns and feed field learnings back into the offering to make delivery repeatable.

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