Executive Summary

We are looking for an innovative Director of Engineering – AI Solutions for Developer Productivity to transform how our software engineers build, test, and deploy code. In this high-impact role, you will lead the strategy and execution of AI-driven platform tools, intelligent coding assistants, automated code review agents, and automated pipeline workflows. Your goal is to build an internal AI ecosystem that removes developer friction, eliminates repetitive tasks, and measurably boosts engineering velocity across our global technology team.

Key Responsibilities

AI Developer Tooling Strategy
•    Internal Platform Roadmap: Define and drive the vision for AI-infused internal developer tools, including LLM code-generation assistants, intelligent CI/CD diagnostic agents, automated code migration tooling, and dynamic documentation systems.
•    Productivity Metrics (Core 4, DORA & SPACE): Use established Developer Experience KPIs to introduce AI initiatives/solutions that increase overall engineering output.

Team Leadership & Platform Delivery
•    Engineering Management: Lead, recruit, and mentor a team of Machine Learning/AI Engineers (builders, scalers and maintainers) to work closely with the Platform Engineers, and DevEx Engineers to develop AI based productivity solution.
•    Ecosystem Integration: Partner with Infrastructure, DevEng, and Security teams to seamlessly integrate AI tools into developer IDEs, version control systems, and CI/CD pipelines.
•    Prompt & Context Architecture: Oversee the architecture of code indexing, vector databases, and Retrieval-Augmented Generation (RAG) pipelines that feed repository context securely into internal LLMs.

Governance, Security & Adoption
•    Code Privacy & Security: Work closely with Security and Compliance to implement AI based solution that enforce guardrails around IP protection, secret scanning, license compliance, and secure code generation.
•    Change Management & Enablement: Champion the adoption of AI tools across engineering teams; establish internal training programs, hackathons, and best practices to help every engineer become an AI-augmented developer.

Qualifications and Skills

Technical Expertise
•    AI & LLM Integration: 3+ years integrating Generative AI, code-trained LLMs, or agentic frameworks such as LangChain, AutoGen, LiteLLM, Kong, TrueFoundry or custom RAG pipelines into practical developer workflows.
•    Software & Platform Foundations: 8+ years of core software engineering experience, with a background in Developer Experience (DevEx), Internal Developer Platforms (IDP), or CI/CD infrastructure.
•    Developer Ecosystems: Deep familiarity with modern IDEs, AI Code Assist, quality and security AI code scanning  tools, AI solutions for test harness, code review, etc. 
•    System Architecture: Solid understanding of vector search engines, embedding models for code representation, and LLM fine-tuning techniques.

Leadership & Soft Skills
•    Leadership Track Record: 5+ years managing engineering teams at the Engineering Manager, Senior Manager, or Director level, with a strong emphasis on platform engineering or internal tooling.
•    Developer Empathy: Passion for developer productivity, developer satisfaction, and eliminating operational friction.
•    Data-Driven Approach: Experience using metrics to measure productivity gains and cost efficiency without compromising code quality or developer well-being.