Job Description
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 (Lang Chain, Crew AI, Lang Graph).
Product Management: Roadmap planning, stakeholder engagement, feature prioritization, and go-to-market strategies.
Cloud & Dev Ops: AWS/Azure/GCP, container orchestration (Kubernetes), CI/CD pipelines.
Azure/GCP Architecture: Design secure, scalable AI solutions leveraging Azure AI Services, Azure Open AI, 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/Dev Ops practices, risk management, and compliance frameworks.
Leadership: Team building, stakeholder management, strategic planning, and delivery governance.
Qualifications
Bachelor’s/Master’s in Computer Science, Data Science, or related field.
8-12 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.
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 (Lang Chain, Crew AI, Lang Graph).
Product Management: Roadmap planning, stakeholder engagement, feature prioritization, and go-to-market strategies.
Cloud & Dev Ops: AWS/Azure/GCP, container orchestration (Kubernetes), CI/CD pipelines.
Azure/GCP Architecture: Design secure, scalable AI solutions leveraging Azure AI Services, Azure Open AI, 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/Dev Ops practices, risk management, and compliance frameworks.
Leadership: Team building, stakeholder management, strategic planning, and delivery governance.
Qualifications
Bachelor’s/Master’s in Computer Science, Data Science, or related field.
8-12 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.
Apply for this Position
Ready to join ? Click the button below to submit your application.
Submit Application