We are seeking a highly experienced Technical Lead - AI-enabled Medical Devices Engineering to drive engineering excellence, AI adoption, solution design, and delivery readiness for global Medical Devices, Digital Health, and Life Sciences clients.

This is a hands-on leadership role for a seasoned engineering skilled who combines deep technical expertise with practical delivery experience. The ideal candidate will actively contribute to architecture reviews, technical solutioning, proof-of-concepts (POCs), AI-led engineering transformation initiatives, reusable accelerator development, and technical governance while mentoring engineering teams and engaging with client stakeholders.

The role offers an opportunity to shape next-generation AI-enabled engineering solutions in regulated healthcare environments.

Key Responsibilities

Technical Leadership & Engineering Excellence

- Lead hands-on technical solutioning and delivery support across Medical Devices, Digital Health, Product Engineering, Software Engineering, Quality Engineering, Verification & Validation (V&V;), and Sustenance Engineering programs.
- Drive architecture reviews, design assessments, proof-of-concepts, feasibility studies, technical estimations, and delivery readiness evaluations.
- Guide teams on scalable architecture, software quality, modular design, maintainability, reliability, cybersecurity awareness, traceability, and performance optimization.
- Identify and mitigate technical risks, project dependencies, integration challenges, and implementation constraints.
- Mentor engineering leads and development teams on technical best practices, estimation methodologies, reusable design patterns, and engineering productivity.

AI-enabled Engineering Transformation

- Identify and implement AI and GenAI use cases across the Software Development Life Cycle (SDLC).
- Drive adoption of:
- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- AI Agents
- Engineering Analytics
- Workflow Automation
- AI-assisted Coding and Testing

- Develop AI-enabled accelerators, demonstrations, proof-of-concepts, and productivity frameworks.
- Collaborate with AI CoEs and delivery teams to accelerate AI adoption and business value realization.
- Ensure Responsible AI principles, including governance, validation, explainability, traceability, security, and human oversight within regulated environments.
- Measure AI impact through productivity gains, quality improvements, defect reduction,



cycle-time acceleration, and engineering efficiency.

Medical Devices Engineering & Quality Focus

- Support product development throughout the medical device lifecycle including requirements, design, development, verification, validation, release, maintenance, and post-market support.
- Promote quality-first engineering practices, including:
- Design controls
- Traceability
- Risk management
- Documentation excellence
- Defect prevention

- Collaborate with software, systems, cloud, cybersecurity, data engineering, V&V;, quality, and regulatory teams.
- Develop reusable accelerators for:

- Requirements traceability
- Design documentation
- Test evidence generation
- Defect analytics
- Engineering dashboards
- Productivity enhancement

- Contribute to engineering transformation strategies balancing compliance, innovation, delivery efficiency, cost optimization, and risk management.

Delivery Governance & Execution

- Drive delivery readiness by validating scope, architecture, estimates, risks, assumptions, dependencies, and acceptance criteria.
- Participate in technical governance reviews, sprint planning, root-cause analysis, issue resolution, and solution validation activities.
- Ensure engineering solutions meet quality, scalability, security, maintainability, and compliance expectations.
- Facilitate seamless transition from solution design to execution through effective technical documentation and implementation guidance.
- Promote engineering standardization through reusable frameworks, templates, best practices, and automation assets.

Client Consulting & Solutioning

- Support customer workshops, technical discovery sessions, architecture discussions, and solution presentations.
- Communicate technical recommendations, AI opportunities, architecture trade-offs, and implementation approaches to both technical and business stakeholders.
- Translate client challenges into engineering roadmaps, MVP strategies, transformation initiatives, and measurable business outcomes.
- Contribute to proposals, solution documentation, technical estimations, implementation roadmaps,



and capability presentations.
- Build trusted relationships with customer engineering, product, quality, and technology leadership teams.

Required Technical Skills

Engineering & Architecture

- Software Architecture & Design Reviews
- Product Engineering
- System Design & Integration
- Proof-of-Concept Development
- Microservices & Cloud-Native Architectures
- Technical Risk Management
- Engineering Governance
- Software Quality & Maintainability
- Reusable Framework Development

AI & Digital Engineering

- Generative AI (GenAI)
- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- AI Agents
- AI-assisted SDLC
- GitHub Copilot / Microsoft Copilot
- Prompt Engineering
- Engineering Analytics
- Workflow Automation
- Responsible AI Practices

Medical Devices & Quality Engineering

- Medical Device Software Development Lifecycle
- Verification & Validation (V&V;)
- Quality Engineering
- Requirements Traceability
- Risk-Based Engineering
- Sustaining Engineering
- Post-Market Support
- Regulatory-Aware Product Development

Consulting & Delivery

- Technical Solutioning
- Delivery Readiness Assessment
- Technical Estimation
- Stakeholder Management
- Technical Workshops
- Root Cause Analysis
- Engineering Transformation Programs
- Client-Facing Consulting

Preferred Industry Experience

Candidates with experience in one or more of the following domains will be preferred:

- Medical Devices
- Digital Health
- Healthcare Technology
- Life Sciences
- Connected Medical Devices
- Quality Engineering
- Verification & Validation
- Regulated Product Development
- Engineering Services
- Product Engineering Organizations

Qualifications

- Bachelor's or Master's Degree in Engineering, Computer Science, Biomedical Engineering, Information Technology, Electronics, or related disciplines.
- 12-18+ years of experience in Medical Devices, Digital Health, Product Engineering, Software Engineering, Quality Engineering, or Technical Leadership roles.
- Demonstrated experience in architecture reviews, engineering governance, delivery leadership, and solution design.
- Exposure to AI/GenAI-driven engineering transformation initiatives.
- Strong understanding of software quality, compliance-focused engineering, and regulated product development environments.
- Excellent communication, stakeholder management, and client engagement skills.

Please share resumes in [email protected]

📌 Technical Lead - AI-enabled Medical Devices Engineering (Maharashtra)
🏢 Capgemini
📍 Maharashtra