AI Led Forward Deployed Engineer | Design & Digital Products

Accenture•Milwaukee, NY

25d•Hybrid

About The Position

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.

Requirements

Minimum 3 years of AI & Data experience, including solutioning, designing, or delivering AI & Data projects, with hands-on work shipping GenAI features (RAG, agentic workflows, evals and guardrails), not strategy decks alone.
Minimum 3 years of high-value consulting experience, including large-scale delivery with minimal oversight and proven ability to lead workstreams and meet deadlines, or relevant industry / functional experience.

Nice To Haves

Hands-on delivery experience on at least one enterprise AI platform in production: AWS Bedrock, Google Vertex AI, Azure AI Foundry, or Databricks Mosaic AI.
Working fluency with GenAI frameworks and patterns: LangChain or LlamaIndex, agentic orchestration (CrewAI / AutoGen), MCP, prompt and context engineering, and model selection across frontier and open-weight models (Claude, Gemini, GPT, Llama, Mistral).
Model judgment: knows when to apply fine-tuning (LoRA / PEFT) vs. prompt engineering vs. RAG, and can reason about cost, latency, accuracy, and compliance tradeoffs.
Product engineering ability: full-stack build of AI-powered digital products, ships working code, and can activate AI against existing enterprise data using data-gravity patterns rather than re-architecting infrastructure.
Product-led mindset: connects AI & data work to product strategy and the design-to-product pipeline, and can originate use cases and shape an engagement before a brief exists.
Experience managing senior stakeholders.
Strong program management and verbal and written communication skills.
Driven and entrepreneurial: ability to originate and shape new deals and lead go-to-market activities.
Excellent leadership and people skills: proven ability to build effective teams, foster collaboration and inclusion, and build strong relationships with stakeholders / clients.

Responsibilities

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 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.