Head of AI Strategy & Delivery

Job Category

We’re looking for a highly technical and visionary Head of AI Strategy & Delivery to define, lead, and scale our company-wide AI efforts. In this role, you’ll shape the long-term AI roadmap, build production-ready AI systems, and drive real business impact across multiple products and teams. This is a hands-on leadership role for someone who can combine strategy, architecture, and execution.

 

Responsibilities

AI Strategy & Impact

• Own the company-wide AI strategy and roadmap, aligned with business goals and product priorities.
• Identify and prioritize high-value AI/GenAI use cases across the organization.
• Define clear success metrics and track measurable impact.
• Evangelize AI internally—helping teams understand where AI creates value and where it doesn’t.

Technical Leadership

• Lead architecture and delivery of production-grade AI systems across a multi-application, multi-tech-stack environment.
• Design end-to-end AI solutions: data pipelines, feature engineering, model development, guardrails, evaluation, deployment, monitoring, and continuous improvement.
• Establish best practices for GenAI safety including privacy, PII handling, prompt integrity, hallucination control, and regulatory compliance.
• Collaborate with Data, Product, Engineering, and Business leaders to translate ideas into scoped, measurable projects.

AI Delivery & Operations

• Oversee AI/ML Ops including CI/CD for models, versioning, experimentation, A/B testing, observability, and incident response.
• Drive “AI in the workflow” initiatives to improve employee productivity—not just prototypes.
• Build and maintain frameworks for AI performance monitoring, model governance, and lifecycle management.

Hands-On Execution

• Prototype rapidly, review architecture and code, and build proof-of-concepts to de-risk ideas.
• Lead and mentor technical leads and AI engineers across multiple initiatives.

Vendor & Ecosystem Management

• Evaluate and manage relationships with model providers, cloud partners, vector databases, annotation tools, and GenAI platforms.
• Apply a disciplined build-vs-buy approach to accelerate delivery while maintaining quality.

Requirements

•    6+ years experience in software engineering, applied AI, or platform engineering roles.
•    3+ years leading AI/LLM initiatives or cross-functional teams in a product-focused environment.
•    Hands-on experience integrating and deploying LLM-based systems (RAG, agents, orchestration, prompt engineering).
•    Strong architecture skills across distributed systems, APIs, and cloud platforms.
•    Familiarity with MLOps/LLMOps concepts (monitoring, versioning, evaluation) — not heavy ML research.
•    Ability to rapidly prototype and de-risk ideas with POCs.
•    Excellent communication skills and the ability to influence cross-functional partners.

Nice to Have

• Experience scaling AI initiatives across a multi-product environment.
• Background taking AI capabilities from zero to one and one to many.
• Familiarity with responsible AI, compliance frameworks, or model risk management.