AI Engineering Manager/ Delivery Lead

IQVIA

Barcelona

Presencial

EUR 90.000 - 130.000

Jornada completa

Hace 2 días
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Descripción de la vacante

IQVIA is seeking an Engineering Manager / Delivery Lead to own end-to-end delivery for Agentic AI solutions within AI & Technology Solutions (ATS) and Clinical AI & Technology Innovation (CAITI). This role orchestrates delivery from PoC to Production, aligning product intent with architectural direction and governance requirements.

The candidate will lead internal teams and external vendors, drive sprint cadence, and ensure quality gates, regulatory compliance, and delivery readiness across

Formación

  • 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 field.
  • Strong understanding of Agentic SDLC / ADLC concepts and agent lifecycle management.
  • Experience delivering agent-based or data-intensive platforms with production readiness, auditability and lifecycle controls.
  • Ability to engage credibly with Solution Architects, Tech Leads, and AI teams on agent feasibility, orchestration complexity, dependency sequencing, and delivery risk.
  • Proficiency in programming languages such as Python, Java, or Scala and solid understanding of data structures and algorithms.

Responsabilidades

  • Own end-to-end delivery execution for Agentic AI solutions from PoC 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 escalating 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: 1) Task integration, 2) Quality expectations, 3) 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.

Conocimientos

Engineering delivery
Agentic AI delivery
Python
Java
Scala

Educación

Bachelor's degree in Computer Science / Information Systems
Master's degree in Computer Science / Information Systems

Descripción del empleo

Role Description

We are seeking an Engineering Manager / Delivery Lead to own end‑to‑end delivery execution for Agentic AI solutions within AI & Technology Solutions (ATS), Clinical AI & Technology Innovation (CAITI). This role is accountable for translating product intent and architectural direction into reliable, compliant, high‑quality delivery outcomes, by leading internal teams and external vendors.


Operating as part of the Core Development Team, the Engineering Manager is the single point of accountability for delivery execution, owning sprint cadence, SDLC deliverables, delivery readiness, and release orchestration from Proof of Concept through Production.


This role works in tight partnership with:
AI Product Manager & Product Owner (value, scope, priorities)
AI Solution Architect & Tech Lead (architecture, patterns, technical direction)
Program Manager (governance, cross‑program alignment, escalation)


while retaining clear decision authority over delivery execution.


Key Responsibilities


  • 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 escalating 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: 1) Task integration, 2) Quality expectations, 3) 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.


Key Qualifications

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, 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.


Scala, with strong understanding of data structures and algorithms.


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 apprec

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