Role Summary :

- Lead enterprise AI solution initiatives combining product vision, technical excellence, and delivery governance.

- Drive architecture, roadmap, and execution for AI-powered products, ensuring measurable business impact, compliance, and scalability.

- Build and mentor high-performing teams while fostering innovation and operational rigor.

Key Outcomes :

- Define and implement AI product strategy aligned to business objectives.

- Deliver enterprise-grade AI applications with clear ROI, reliability (SLOs), and security.

- Establish best practices for IT delivery, observability, and compliance.

- Build and lead cross-functional teams; enable collaboration between engineering, product, and operations.

Responsibilities :

- Product Management : Own AI product lifecycle from ideation to deployment; define roadmaps, prioritize features, and ensure user-centric design.

- Gen-AI Solutions : Architect and deliver Generative AI applications leveraging LLMs, multi-agent systems, and orchestration frameworks.

- Team Management : Build, mentor, and scale high-performing teams across engineering and product functions.

- IT Delivery : Ensure robust delivery governance, cost optimization, and adherence to SLAs/SLOs for enterprise AI systems.

- Translate business challenges into scalable AI architectures and actionable roadmaps.

- Collaborate with Product, Security, Compliance, and Ops teams to ensure safe-by-default systems.

- Manage vendor relationships and evaluate emerging AI technologies for strategic fit.

Technical & Leadership Skills :

- AI/ML Expertise : Agentic AI, Generative AI, Conversational AI, orchestration frameworks (LangChain, CrewAI, LangGraph).

- Product Management : Roadmap planning, stakeholder engagement, feature prioritization, and go-to-market strategies.

- Cloud & DevOps : AWS/Azure/GCP, container orchestration (Kubernetes), CI/CD pipelines.

- Azure/GCP Architecture : Design secure, scalable AI solutions leveraging Azure AI Services, Azure OpenAI, Cognitive Services, Event Grid, AKS; Architect GCP-based AI platforms using Vertex AI, Pub/Sub, GKE, Cloud Functions, and implement cost governance.

- MLOps : Model lifecycle management, observability, governance, and cost optimization.

- IT Delivery : Agile/DevOps practices, risk management, and compliance frameworks.

- Leadership : Team building, stakeholder management, strategic planning, and delivery governance.

Qualifications :

- Bachelors/Masters in Computer Science, Data Science, or related field.

- 8 to 12 years of experience in AI/ML solution delivery, product management, and IT governance.

- Proven track record of deploying and operating AI systems at scale.

- Strong programming background (Python preferred) and familiarity with modern AI ecosystems.