Forward Deployed AI Engineer

About the role

Forward Deployed AI Engineer

Location: Westchester, IL (Chicago area) — hybrid, onshore

Engagement: 12 months, extendable

Start: Early October 2026

THE OPPORTUNITY

This role is the onshore engineer who turns that backlog into a governed, value-ranked pipeline of production AI agents — building on what Client’s has already started with Ask Client’s, manufacturing AI/ML and its Microsoft and SAP estate. You sit inside Client’s business and technology teams, run rapid 4–6-week assessments, set the architecture and governance standards, and direct an offshore delivery pod that builds to them. You are accountable for the first wave of agents reaching production, being adopted, and being measurable.

WHAT YOU WILL OWN

Backlog to pipeline — triage the ~150 opportunities for business value and technical feasibility, run 4–6-week rapid assessments on 1–3 candidates at a time, and convert them into a funded delivery roadmap through year-end and beyond.

Solution patterning — map each opportunity to an Assist (knowledge and chat), Act (human-in-the-loop execution) or Decide (higher-autonomy) agent pattern, and build the reusable templates that make every subsequent use case faster to deliver.

Standards and governance — define the orchestration, context, guardrail, cost-control and observability standards for all agents, and ratify them with enterprise architecture, IT and security leadership including the CISO.

Architecture — design on an Azure-centric stack, integrating with Microsoft 365 Copilot and Teams and with core systems including SAP, MyClient’s and the Power BI/analytics estate. Avoid net-new tooling unless a capability gap requires it; contribute to evaluation of orchestration, control/observability and common front-end platforms.

Delivery leadership — lead the offshore engineering pod in a factory/lab model — set the technical bar, review builds, unblock, and scale capacity with the use-case count.

Stakeholder and value management — run workshops with process, supply chain, finance and plant stakeholders; define success metrics and report adoption, ROI and delivery outcomes to executive sponsors.

WHAT YOU BRING

8+ years in enterprise technology delivery, with 3+ years building AI/GenAI or intelligent automation solutions in client-facing or embedded roles.

Hands-on depth in LLMs, agent frameworks, RAG, orchestration, evaluation and enterprise API integration. Azure OpenAI / Azure AI Foundry experience strongly preferred.

Demonstrated ownership of AI governance and observability in production: tracing, evals, guardrails, human-in-the-loop design, and cost control.

Manufacturing, CPG, food and ingredients, or process-industry domain experience — able to hold a credible conversation about plant, supply chain and quality operations.

Strong business analysis and requirements skills, and the judgment to balance value, feasibility, cost, risk and time-to-value.

Experience leading distributed offshore engineering teams across time zones; comfortable on-site in the Chicago area.

FIRST 90 DAYS — WHAT GOOD LOOKS LIKE

Rapid assessments complete for the first 1–3 projects, each with a costed build plan and named business owner.

Governance, observability and architecture standards documented and signed off by enterprise IT and security.

First Assist and Act agents in production with measured adoption, and reusable templates handed to the offshore pod.