Senior Director Software Engineer, AI Engineering - DEX Products

We are building a portfolio of agentic operations — production-grade AI agents that plan, act, and continuously improve the everyday experiences of our employees. The goal is simple and ambitious: eliminate friction from the moments that matter so employees spend more time on work that matters and less time on tickets, forms, and queues.

As Executive Director, Software Engineer, you will own the end-to-end technical direction and hands-on architecture of the Digital Employee Experience and the flagship agents built on it. You will lead a multi-disciplinary engineering group , partner with product, IT, cyber, and controls, and be personally accountable for the reliability, safety, cost, and business outcomes of every agent that reaches employees.

This is a hands-on senior engineering leadership role: you will write code, design systems, run production, and set the technical bar — while coaching a team of engineers across squads.

Job responsibilities

• Own the reference architecture for agentic operations: orchestration, planning, tool-use, memory, retrieval (RAG / GraphRAG), evaluation, guardrails, observability, human-in-the-loop, cost governance, and lifecycle (build → evaluate → deploy → monitor → retire).

• Choose and evolve the stack (agent frameworks, model gateway, vector stores, feature/knowledge stores, workflow/queue, telemetry, red-team & eval harness). Balance make-vs-buy against firm standards and controls.

• Define the golden path so any employee-experience squad can ship a safe, evaluated agent in weeks — not quarters.

Flagship employee-experience agents

• Ship agents that measurably deflect / auto-resolve high-volume employee journeys, e.g. IT service desk incidents, access & entitlements.

• Design multi-agent and human-in-the-loop patterns that know when to act, when to draft, and when to escalate.

• Instrument every agent with business KPIs (deflection rate, time-to-resolve, CSAT, cost per interaction) and quality KPIs .

Reliability, safety, and controls

• Establish SRE for agents: SLOs, error budgets, canaries, circuit breakers, prompt/model version pinning, deterministic replay, rollback.

• Partner with cybersecurity, privacy, model risk, controls, and audit to make responsible AI concrete: data minimization, purpose limitation, PII handling, evaluation before change, model & prompt inventory, drift detection, red-teaming, jailbreak defense, secret and tool-use hygiene.

• Own the evaluation harness: offline benchmarks, online A/B, gold sets, LLM-as-judge with human calibration, regression gates in CI/CD.

Delivery leadership

• Lead squads via principal/lead engineers; set the technical bar via architecture reviews, code quality standards, and design docs.