16 Sep
|
Capgemini
|
Bengaluru
16 Sep
Capgemini
Bengaluru
Role & responsibilities The Solution Delivery Leader represents a fundamental shift in how we define delivery excellence. As software moves from a structured SDLC to continuous, AI-powered engineering cycles, quality can no longer be a downstream activity it must be designed, engineered, and continuously validated in real time within the lifecycle.
This role is designed to bridge the gap between client problems and engineering solutions. You will not be measured by execution alone, but by your ability to shape solutions, influence engineering leaders, and bring AI-led innovation to life.
You are the face of technology-driven delivery, helping clients transition from testing services to intelligent, always-on quality engineering ecosystems.
Preferred candidate profile
AI-Powered Delivery & Continuous Quality Engineering (40%)
What you will do:
- Embed continuous validation within CI/CD pipelines, ensuring quality is always on
- Use GenAI and intelligent automation to transform how testing is designed, executed, and optimized
- Shift teams from manual validation to engineering-led, AI-assisted quality systems
- Build predictive and preventative quality models, reducing defects before they occur
2. Solutioning, Innovation & Client Co-Creation (35%)
What you will do
- Work directly with CTOs and Engineering Heads to understand real problemsnot just stated requirements
- Demonstrate solutionsthrough PoCs, accelerators, and live demos (show, not tell)
- Build AI-first transformation roadmaps aligned to business outcomes
- Bring together partner ecosystems (AI platforms, hyperscalers, tooling providers) to create differentiated solutions
3. Technology Leadership & Transformation Governance (15%)
What you will do:
- Anchor discussions in engineering, architecture, and AI adoption
- Define and track engineering KPIs tied to business value
- Ensure solutions are scalable, feasible, and commercially viable
- Guide clients through measurable transformation journeys, not one-off improvements
4. Talent & Capability Evolution (10%)
What you will do:
- Build AI-first engineering capabilities across teams
- Mentor talent to move from QA roles to Solution Engineers and AI-enabled QE specialists
- Drive a culture of engineering ownership, innovation, and continuous learning
Core Skills & What Sets You Apart
- AI-Native Mindset: Hands-on experience with GenAI, LLMs, Copilot, and intelligent automation
- Solution Thinking: Ability to translate ambiguous client problems into structured, scalable solutions
- Engineering Depth: Strong grasp of cloud, microservices, DevOps, and observability
- Client Influence: Confidence to engage and challenge senior engineering stakeholders
- Demonstration Ability: Ability to build and showcase working solutions, not just conceptual ideas
A Sample Day in the Life Bringing It All Together
- Start with AI-driven quality insights and release health signals
- Engage a client engineering leader to shape a transformation roadmap
- Demo a GenAI-powered solution or accelerator to stakeholders
- Align internal teams on delivering continuous quality in live pipelines
- Coach teams on AI adoption and next-gen engineering practices
Perks and perks
- Lead with engineering and technologynot operations
- Solve client problems, not just delivery scope
- Use AI as a core lever of transformation
- Drive measurable business and engineering outcomes
- Build credibility as a trusted advisor to engineering leadership
📌 AI QA Automation Delivery lead (Bengaluru)
🏢 Capgemini
📍 Bengaluru