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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
