Director, AI Technical Delivery & Standards

Role Summary

The Director, AI Technical Delivery & Standards is the technical anchor of the central AI Transformation Office. The role owns the technical integrity of what the central team delivers and the standards every AI solution must meet: the AI development lifecycle, reference-architecture conformance, evaluation and quality benchmarks, and validation and model-governance readiness. Adoption and enablement remain with the workstreams and functional areas that own their people and processes - this role ensures that what they adopt is technically sound, evaluated, and built to last.

Key Responsibilities

• AI SDLC ownership - own the central view of the AI development lifecycle (AI SDLC) - intake through build, evaluation, validation, deployment, and monitoring - and drive its consistent adoption across teams building AI solutions.
• Reference architecture alignment - work with the development architecture workstream to ensure programs and projects conform to the enterprise AI reference architecture; flag divergence early and broker pragmatic resolutions.
• Validation & model governance - drive clarity of ownership for AI solution validation; partner with quality, regulatory, and healthcare-grade AI stakeholders to make validation a designed-in step rather than a late-stage blocker.
• Solution delivery oversight - provide hands-on technical direction for centrally delivered AI solutions - prompt and evaluation design, RAG and agentic patterns, integration approaches, human-in-the-loop design - and review technical proposals from vendors and internal teams.
• Evaluation & quality - define how AI solutions are evaluated - accuracy, safety, cost, latency, and fitness for purpose - build reusable evaluation harnesses and benchmarks, and set the quality bar a solution must clear before it scales.
• Bilingual communication - act as translator between engineering, data science, and business leadership - making technical trade-offs legible to executives and business constraints legible to builders.

Required Qualifications

• 10+ years across software delivery, data/ML engineering, solution architecture, or technical program leadership, including 3+ years working directly with AI/ML or GenAI solutions.
• Applied understanding of LLM-based systems: prompting and evaluation, retrieval-augmented generation, agentic workflows, fine-tuning trade-offs, and API/platform integration patterns.
• Experience operating within or alongside an SDLC in a regulated or quality-managed environment; comfort with validation, documentation, and auditability requirements.
• Track record of technical governance without bottlenecking delivery - standards that teams adopt because they help.
• Credibility with both engineering teams and senior business stakeholders.

Preferred Qualifications

• Hands-on experience with major AI platforms and model providers (e.g., Anthropic, OpenAI, Azure AI, AWS Bedrock, NVIDIA stack) and modern data platforms.
• Life sciences / healthcare technology background; exposure to GxP or healthcare-grade AI expectations.
• Prior architecture, data science, or engineering management role before moving into transformation leadership.

Success Looks Like (First 12 Months)

• A single, adopted AI SDLC standard with clear validation ownership at each stage.
• Central programs and special projects pass architecture and validation checkpoints without late-stage rework.
• Technical workstream leaders treat the central team as a peer contributor, not an administrative layer.

IQVIA is a leading global provider of clinical research services, commercial insights and healthcare intelligence to the life sciences and healthcare industries. We create intelligent connections to accelerate the development and commercialization of innovative medical treatments to help improve patient outcomes and population health worldwide. Learn more at https://jobs.iqvia.com

IQVIA is committed to integrity in our hiring process and maintains a zero tolerance policy for candidate fraud. All information and credentials submitted in your application must be truthful and complete. Any false statements, misrepresentations, or material omissions during the recruitment process will result in immediate disqualification of your application, or termination of employment if discovered later, in accordance with applicable law. We appreciate your honesty and professionalism.