Director, AI First Engineering

Director, AI First Engineering

Chicago, Illinois

Direct Hire

Salary Range : $190,000 - $230,000

Benefits :
Full benefits start on day 1

Company provides an employer match to employee 401(K) contributions by matching 75% of employee contributions on up to 6% of eligible earnings,FTO - flexible time off - no limit

Industry-leading benefits plans

Director, AI Enterprise Engineering
Our client is a well-established, PE-backed technology company with operations spanning North America, Europe, and Asia. They serve a global customer base through a portfolio of software platforms, financial tools, and operational services. The engineering organization is undergoing a full transformation to an agentic, AI-driven delivery model, and this role sits at the center of executing that shift.

As Director, AI Enterprise Engineering, you drive the adoption of modern AI engineering practices across the software engineering organization, converting the company’s investment in agentic development tooling into repeatable, governed, and measurable engineering outcomes. This is a hands‑on engineering leadership role reporting to the SVP of Engineering.

You will directly manage a distributed team of solution architects, engineers, and verification architects spanning onshore and offshore operations. You own hiring, coaching, performance management, and the operating cadence that keeps an agentic, spec‑driven delivery model moving in tight build‑measure‑learn cycles.

The right candidate combines strong engineering fundamentals, modern Microsoft‑stack delivery experience, hands‑on agentic AI and multi‑agent systems experience, and proven change leadership. Success is measured by outcomes: what the team ships, its reliability and business impact, adoption maturity, and the trust the business places in engineering.

• Define and execute the team’s delivery roadmap, using agentic development and AI coding tooling as core capabilities, partnering with Product and the business to prioritize and evolve applications over time.
• Embed AI across the full delivery cycle: spec-driven intent, agent execution (plan, build, and test), automated verification quality gates, and production insight that feeds learnings back into the context store, while engineers remain accountable for intent, architecture, quality, and release decisions.
• Hold final accountability for the reliability, accuracy, and business impact of what the team ships, including AI agents, LLM‑powered features, and automation built into applications in scope.
• Partner with peer engineering and architecture leaders to align on shared standards, roadmap, and reusable patterns.
• Stay close enough to the work to prototype, review examples, challenge assumptions, and demonstrate credible hands‑on engineering judgment.

• Directly manage a high‑performing engineering team, owning hiring, onboarding, performance management, and individual career development.
• Run a single operating model across onshore and offshore delivery capability, with time‑zone‑aware rituals and communication practices that make a global team operate as one.
• Coach Solution Architects to set direction and mentor the rest of the team. Build collective AI engineering capability through structured learning paths, enablement sessions, champions, office hours, and communities of practice.
• Set direction collaboratively: frame options, integrate team input, commit to clear objectives and owners, and drive them to completion.

• Drive responsible enterprise adoption of AI coding tooling — onboarding, usage patterns, repository context, guardrails, training, and coaching —…