Lead AI Engineer / AI Evangelist, Healthcare Business Unit (EMEA)

Job Description

Requirements:
 

• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field.
   
• 5+ years in software engineering, technical leadership, or developer experience roles, with recent hands-on exposure to GenAI-assisted development.
   
• Demonstrated track record of introducing new tools, practices, or methodologies across engineering teams and measuring adoption.
   
• Hands-on proficiency with AI coding assistants and agentic dev tools (e.g., Claude Code, GitHub Copilot, Cursor, Windsurf, Cline) and ability to evaluate them critically.
   
• Solid understanding of modern SDLC practices: code review, CI/CD, test automation, requirements management, and release engineering.
   
• Working knowledge of LLM fundamentals: prompting, context management, retrieval-augmented generation, evals, model selection, and cost/latency trade-offs.
   
• Familiarity with MCP, agent frameworks, and integrating AI tools with existing engineering systems (Jira, GitLab/GitHub, Confluence, ALM tools).
   
• Strong communication, facilitation, and storytelling skills — comfortable presenting to engineers, architects, delivery managers, and client executives.
   
• Ability to define adoption metrics (productivity, quality, cycle time) and run structured pilots that produce defensible results.
   
• English proficiency at Upper-Intermediate level or higher.

Preferred Qualifications (Nice to Have)
 

• Experience introducing AI tooling into a regulated SDLC (IEC 62304, ISO 13485, FDA design controls, GxP, or equivalent).
   
• Familiarity with healthcare-specific constraints on AI use: PHI handling, HIPAA, GDPR, FDA AI/ML guidance (including PCCP), and EU AI Act / MDR implications for development workflows.
   
• Prior involvement in presales, proposal writing, or client technical advisory.
   
• Experience standardizing prompts, skills, or reusable AI assets across multiple delivery teams.
   
• Background in developer advocacy, technical enablement, or internal evangelism programs.
   
• Awareness of test-generation, code-review, and documentation use cases that intersect with regulated traceability requirements.
   

Job Responsibilities

• Lead the introduction and scaling of AI-assisted SDLC practices across HealthTech and MedTech delivery teams.
   
• Identify, evaluate, and pilot AI tools (coding assistants, agentic systems, AI-driven QA, documentation, and requirements tools) and produce clear go/no-go recommendations.
   
• Define and standardize prompts, skills, playbooks, and reusable assets that teams can adopt without reinventing the wheel.
   
• Embed with project teams to coach engineers, architects, and QA on practical, day-to-day AI usage — moving from demos to durable workflow change.
   
• Establish adoption KPIs, run controlled pilots, collect evidence, and report measurable impact on productivity, quality, and time-to-delivery.
   
• Partner with delivery and engineering leadership to integrate AI tooling into existing processes (code review, test management, documentation, traceability) without breaking compliance posture.
   
• Work with InfoSec, Legal, and Compliance to ensure AI usage respects PHI/PII handling, IP, client data agreements, and regulated SDLC constraints.
   
• Support technical presales: shape AI-in-SDLC narratives, contribute to proposals, and present to client engineering and executive audiences.
   
• Run internal enablement: workshops, brown-bags, office hours, and accountability-driven adoption meetings.
   
• Contribute to GlobalLogic's healthcare-focused AI accelerators, internal knowledge bases, and the Architects Team's shared body of practice.
   
• Track the external landscape (model releases, tooling, regulatory signals) and translate it into actionable guidance for delivery teams.
   

Department/Project Description
 

Join GlobalLogic’s Architects Team within the Healthcare Business Unit, supporting clients across the EMEA region. This strategic role focuses on engaging new clients, solving real-world healthcare challenges, and launching data-driven AI/ML projects. You will work closely with clients and internal stakeholders to translate complex business needs into impactful data science solutions. If you’re passionate about applying data science in a meaningful domain and want to shape the future of healthcare, we’d love to hear from you.