AI Engineering Manager/ Delivery Lead

IQVIA is a leading global provider of clinical research services, commercial insights and healthcare intelligence to the life sciences and healthcare industries. They focus on accelerating the development and commercialization of innovative medical treatments to improve patient outcomes and population health worldwide.

Experience:

• 7+ years in engineering delivery roles, with demonstrated ownership of end‑to‑end delivery in complex systems.
• Proven experience delivering Agentic AI, AI‑enabled, or data‑intensive platforms, including systems that incorporate reasoning, orchestration, retrieval, or automation components.
• Experience delivering AI solutions in regulated or highly governed enterprise environments, with accountability for production readiness, auditability, and lifecycle controls.
• Demonstrated ability to coordinate cross‑functional teams and external vendors delivering agent‑based solutions across prototype, MVP, and production stages.

Technical & Delivery Background:

• Bachelor’s degree with 10+ years of experience, or Master’s degree with 7+ years of experience in Computer Science, Information Systems, or a related technical field.
• Strong understanding of Agentic SDLC / ADLC concepts, including agent lifecycle management and phased progression.
• Experience delivering systems that require agent evaluation, monitoring, and feedback loops, including performance, reliability, and behavioral drift considerations.
• Ability to engage credibly with Solution Architects, Tech Leads, and AI teams on agent feasibility, orchestration complexity, dependency sequencing, and delivery risk.
• Practical understanding of CI/CD for agentic systems, including environment readiness, controlled releases, rollback strategies, and post‑deployment monitoring.
• Proficiency in programming languages such as Python, Java, or Scala, with strong understanding of data structures and algorithms.

• Own end‑to‑end delivery execution for Agentic AI solutions from Proof of Concept through Production, ensuring predictable, high‑quality outcomes.
• Translate product scope and architectural direction into clear delivery plans, sprint cadence, and execution milestones.
• Drive day‑to‑day engineering delivery, including dependency management, issue resolution, and removal of execution blockers.
• Ensure delivery readiness across environments, CI/CD, quality gates, validation, and release governance.
• Coordinate and orchestrate internal teams and vendors to deliver as a single, integrated delivery unit.
• Partner closely with Product, Architecture, QA, Validation, and Program Management to ensure delivery aligns with regulatory, quality, and governance expectations.
• Provide transparent delivery reporting, proactively surface risks, and escalate issues with clear options and trade‑offs.
• Support release and rollout execution (pilot to scale) and ensure effective handover to operations.
• Lead and mentor a multidisciplinary engineering team (AI engineers, data engineers, platform engineers), providing technical guidance, career development, and performance management.
• Act as delivery owner for vendor‑contributed work, including task integration, quality expectations, and delivery timelines.
• Ensure vendor outputs meet IQVIA standards and are integrated seamlessly into CI/CD and release processes.
• Surface delivery risks related to vendor dependency early and clearly.

IQVIA maintains a zero tolerance policy for candidate fraud. All information and credentials submitted must be truthful and complete. False statements, misrepresentations, or material omissions during recruitment will result in disqualification or termination of employment according to applicable law.