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AI Lead

Alira Health -
Barcelona, Barcelona provincia

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Detalles del empleo

Jornada completa

Cualificaciones

CI/CD
Azure
Doctorado
Informática
Máster
AWS
Escalabilidad
Cloud
Inteligencia artificial

Descripción completa del empleo

Are you being referred to one of our roles by a connection in Alira Health? If so, please apply using the referral link emailed to you.

Join our global team dedicated to innovation and initiative, where physical walls and different time zones don’t limit, but encourage, collaboration. Where all contributions and new ideas are explored with an open mind and work is driven by our shared values: be courageous, be accountable, be honest, be inclusive and elevate others.

Job Description Summary

Job Description

The AI Lead is accountable for defining and executing Alira Health’s AI strategy and adoption roadmap across IEC and EVG, ensuring alignment with business priorities, data privacy requirements, and governance standards appropriate for regulated life sciences work.

This role leads the practical integration of AI assistants and agentic workflows into day-to-day business processes, with a specific focus on scalable operational enablement, system reliability, and end-to-end ownership of data and AI solutions.

In addition to strategy and governance, this role is responsible for the design, delivery, and operation of scalable data and AI systems, ensuring initiatives are built on robust, production-ready platforms.

The AI Lead oversees a focused team of Data and AI Engineers and is accountable for both what is built (strategy, prioritization) and how it is built and operated (architecture, engineering, and delivery).

Key Responsibilities

AI Strategy, Portfolio & Delivery Model

Define and maintain the enterprise AI roadmap and long-term development strategy based on validated requirements and feasibility assessments
Drive structured intake, prioritization, and sequencing of AI use cases in partnership with PMO and business stakeholders
Ensure alignment between AI initiatives and business value, data availability, and technical feasibility

Data & AI Platform Ownership

Own end-to-end architectures for AI solutions leveraging current company stack (Azure, Snowflake)
Design and implement scalable data platforms(data ingestion, transformation, storage, serving) for AI application
Ensure production-grade reliability, monitoring, alerting
Define and enforce engineering standards for scalability and performance

Engineering Leadership

Lead and mentor a team of Data and AI Engineers
Set technical direction and guide architecture decisions
Conduct design reviews and ensure high-quality engineering practices
Build a strong engineering culture focused on ownership and delivery

AI Governance, Risk Management & Compliance

Implement a centralized AI governance model aligned with business strategy, data security, and compliance expectations
Ensure governance supports scalable delivery without blocking engineering velocity
Define data governance foundations (access boundaries, confidentiality, compliance constraints)
Ensure feasibility checks are performed (data availability, technical constraints, readiness)

Operational Enablement & Performance Measurement

Establish standardized adoption frameworks, training programs, and guidance materials
Ensure systems are measurable with clear KPIs on performance, reliability, and business impact
Provide structured reporting on delivery progress, risks, and outcomes

Desired Qualifications & Experience

Master’s degree (preferred) in Computer Science, Data Science, Engineering, or related field (PhD a plus)
5 years of experience across data science/ML, analytics, or AI delivery, including 2+ years leading teams
Proven experience designing and operating production data and ML systems at scale
Experience leading Data Engineering / MLOps / ML Engineering teams
Experience in consulting or professional services is preferred, ideally within healthcare or life sciences environments
Demonstrated experience implementing AI governance in regulated environments
Proven cross-functional leadership with IS&T/IT, PMO, Operations, and business stakeholders

Technical Competencies

Strong applied Generative AI and agentic workflows understanding plus practical implementation oversight
Deep experience with software, data and AI engineering practices (solution design, infrastructure-as-a-code, CI/CD, AI observability)
Strong experience with data platforms, distributed systems, and scalable pipelines
Strong grasp of data and AI regulations
Experience with cloud platforms (Azure, AWS), orchestration tools, and modern data stacks

Soft Skills

Executive presence and strong influence across practices and functions
High judgment and risk awareness
Structured, pragmatic operator focused on delivery and outcomes
Strong coaching and enablement orientation

Languages

English

Education

Masters of Science (MS): Computer and Information Science, Masters of Science (MS): Data Processing, Masters of Science (MS): Engineering

Contract Type

Regular

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