Senior Director Software Engineer, AI Engineering

About the role

Lead the technical direction and hands‑on architecture of the Digital Employee Experience (DEX) platform and its flagship AI agents. You will own end‑to‑end reliability, safety, cost, and business outcomes while coaching a multidisciplinary engineering team.

Key responsibilities

• Define and own the reference architecture for agentic operations, including orchestration, planning, tool use, memory, retrieval, evaluation, guardrails, observability, human‑in‑the‑loop, cost governance and lifecycle management.
• Choose, evolve, and balance the technology stack (agent frameworks, model gateways, vector stores, feature/knowledge stores, workflow/queue, telemetry, red‑team and evaluation harnesses) against firm standards.
• Enable any employee‑experience squad to ship a safe, evaluated agent in weeks by establishing a golden path and SRE practices (SLOs, error budgets, canaries, circuit breakers, deterministic replay, rollback).
• Partner with cybersecurity, privacy, model risk, and audit teams to implement responsible AI controls such as data minimisation, PII handling, model version pinning, drift detection and jailbreak defence.
• Lead engineering squads, set technical standards through architecture reviews and design docs, and grow senior talent while maintaining a strong hiring bar.

Required profile

• 12+ years of software engineering experience, including 5+ years leading engineers and 3+ years shipping production ML/AI systems, with at least 1 year delivering LLM‑ or agent‑based products to real users.
• Proven track record designing and operating large‑scale distributed systems in production (SLOs, on‑call, incident command, cost management).
• Executive‑level communication skills, able to convey technical trade‑offs to senior business stakeholders.

Required skills

• Deep hands‑on expertise in at least one modern language: Python, TypeScript, Java or Go.
• Experience with agentic stacks: LLM orchestration frameworks (LangGraph, LlamaIndex, Semantic Kernel or custom), tool/function calling, Retrieval‑Augmented Generation, evaluation harnesses, prompt and model versioning, model gateways.
• Strong grounding in data platforms (Databricks, Snowflake, lakehouse patterns), event streaming, and modern MLOps/LLMOps (CI/CD, feature/prompt/model registry, observability).
• Leadership in responsible AI, security and controls for enterprise deployments (PII/PCI/PHI handling, red‑team, jailbreak defence, secret hygiene).