JD - Technical Lead - AI-enabled Medical Devices Engineering

Medical Devices & Life Sciences | Mumbai, Pune, Gandhinagar, Bangalore / Hybrid

Role Summary The Senior Manager / Hands-on Technical Lead - AI-enabled Medical Devices Engineering will lead and support technical execution, solution design, AI adoption, delivery readiness, and engineering transformation initiatives for Medical Devices and Life Sciences clients.

The role is intended for a practical engineering leader who remains close to architecture, design reviews, proof-of-concepts, reusable accelerators, estimation, technical risk management, and team mentoring while also supporting customer-facing solution conversations when required.

The individual will collaborate with delivery teams, solution architects, AI specialists, quality and regulatory-aware SMEs, and client stakeholders to create scalable, compliant, productivity-focused, and delivery-ready engineering solutions.

Key Responsibilities

Hands-on Technical Leadership

- Lead hands-on technical solutioning and delivery support for Medical Devices, Digital Health, product engineering, software engineering, quality engineering, V&V; and sustaining engineering initiatives.
- Contribute directly to architecture decisions, design reviews, POCs, technical feasibility analysis, estimation baselines, reusable components and delivery-readiness reviews.
- Guide teams on maintainable design, modularity, code quality, performance, reliability, cybersecurity awareness, traceability and supportability.
- Review technical risks, assumptions, dependencies, tooling choices, integration points and delivery constraints before implementation or proposal handover.
- Mentor technical leads and engineers in engineering discipline, documentation quality, estimation accuracy, reusable design and problem-solving practices.

AI-enabled Engineering Transformation

- Identify GenAI and AI use cases across requirements analysis, design documentation, software development, unit testing, test automation, defect analytics, knowledge retrieval, quality engineering and post-market support.
- Shape practical AI-enabled productivity solutions using LLMs, RAG, AI agents, workflow automation, engineering analytics and AI-assisted SDLC approaches.
- Collaborate with AI CoEs and delivery teams to develop demos, POCs, accelerators, adoption roadmaps and business cases for AI-led engineering transformation.
- Embed responsible AI considerations including data sensitivity, traceability, validation, explain ability, governance and human-in-the-loop review for regulated contexts.
- Quantify AI value in terms of productivity, cycle-time reduction, quality uplift, faster documentation, knowledge reuse,



defect prevention and compliance-readiness.

Medical Devices Product Engineering & Quality Focus

- Support medical-device engineering across concept, development, verification, validation, release, maintenance, sustenance and post-market quality phases.
- Bring quality-first engineering practices into solution design, including traceability, risk awareness, documentation discipline, defect prevention and release-readiness thinking.
- Collaborate with software, embedded, systems, cloud, data, cybersecurity, V&V;, quality and regulatory SMEs to shape integrated engineering solutions.
- Help build accelerators for requirements traceability, design documentation, test evidence, defect analytics, engineering dashboards, reusability and productivity improvement.
- Contribute to pragmatic transformation roadmaps balancing innovation, compliance, cost, reuse, risk and delivery execution.

Delivery Readiness & Execution Governance

- Drive delivery readiness by clarifying scope, architecture, estimates, dependencies, risks, assumptions, acceptance criteria and success measures.
- Participate in technical governance reviews, sprint planning support, design walkthroughs, issue triage, root-cause analysis and solution validation.
- Ensure technical decisions are aligned with quality, scalability, security, maintainability, regulatory expectations and customer outcomes.
- Support transition from solutioning to delivery through clear documentation, implementation guidance and technical handover.
- Promote reusable frameworks, engineering templates, automation assets and lessons learned across teams.

Client-facing Technical Contribution

- Support customer workshops, technical deep-dives, solution walkthroughs and capability presentations when hands-on technical credibility is required.
- Explain technical choices, AI opportunities, architecture trade-offs and delivery implications in a clear and business-friendly manner.
- Help translate customer pain points into engineering workstreams, MVP plans, productivity levers and measurable outcomes.
- Contribute to proposal sections, technical assumptions, proof-points, demo narratives and implementation roadmaps.
- Build trust with client engineering stakeholders through practical, delivery-grounded solution recommendations.





Core Skills Hands-on Engineering

AI-enabled SDLC

Medical Devices & Quality

Delivery & Solutioning

- Architecture and design reviews

- POC and prototype development
- Code quality and maintainability mindset
- Technical risk and dependency management
- Integration and data-flow awareness
- Reusable component and accelerator thinking
- GenAI use-case framing
- LLMs, RAG and AI agents awareness
- AI-assisted development and documentation
- AI-assisted testing and defect analytics
- Prompt engineering and Copilot-style adoption
- Responsible AI and human review

- Medical device lifecycle awareness
- Quality-first engineering practices
- V&V; and release-readiness orientation
- Requirements traceability and documentation
- Risk-based engineering mindset
- Sustaining and post-market support awareness

- Technical solution storytelling
- Estimation and delivery-readiness inputs

- Client technical workshops support
- Issue triage and root-cause analysis

- Governance and stakeholder coordination

- Implementation roadmap development

Preferred Experience

- Medical Devices, Life Sciences, Digital Health, product engineering, quality engineering, V&V;, sustaining engineering or regulated delivery exposure.
- Experience leading hands-on technical teams, design discussions, delivery execution, technical governance or engineering transformation initiatives.
- Exposure to AI / GenAI, automation, analytics, AI-assisted SDLC, test automation, documentation acceleration or digital engineering productivity initiatives.
- Ability to translate technical problems into feasible architectures, execution plans, reusable assets and measurable engineering outcomes.
- Experience collaborating with delivery, solution, quality, regulatory, software, systems and AI specialist teams.
- Strong communication skills to support client-facing technical discussions and leadership-ready solution narratives.

Required Qualifications

- Bachelor's or Master's degree in Engineering, Computer Science, Technology, Biomedical Engineering or a related discipline.
- 12-18+ years of experience in engineering services, product engineering, medical devices, Life Sciences, software delivery, quality engineering or related technical leadership roles.
- Proven ability to guide technical teams, review solution designs, manage delivery risks and contribute to practical implementation decisions.
- Robust written and verbal communication skills for technical documentation, design walkthroughs, proposal inputs and stakeholder communication.
- Working knowledge of quality-oriented engineering practices and regulated delivery expectations.

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