Job Role & responsibilities:-

- Lead and deliver AI projects to production end-to-end, ensuring alignment with business expectations and strategic priorities across the insurance value chain
- Define project roadmaps, success metrics, and KPIs (business, technical and operational) for AI use cases, and track them throughout the lifecycle
- Evaluate and prioritize business cases for recent AI requirements, assessing feasibility, expected impact, and ROI
- Work closely with business stakeholders to translate business problems into AI solutions and ensure that delivered products meet value, quality, and time to market expectations
- Oversee the implementation of AI solutions by guiding AI engineers / data scientists / MLOps engineers,while remaining hands?on enough to review designs, pipelines and model performance
- Ensure robust MLOps / AIOps practices for model deployment, monitoring, incident management, and continuous improvement in production environments
- Assess and drive the performance, efficacy, and adoption of AI solutions, and identify opportunities for optimization or scale up
- Collaborate with platform and DevOps teams to ensure AI solutions are deployed using best practices on Azure, Databricks, OpenShift, MLFlow, and/or Azure ML

Technical Skills, Experience & Qualification required:-

- 810 years of progressive experience in Data, AI and ML, including:
- Minimum 23 years specifically in AI project or product leadership (AI Product Lead, AI Delivery Lead, Tech Lead, or similar role)
- Demonstrated experience leading and delivering multiple AI projects to production end-to-end




- Experience in deploying and managing AI models in production environments using Databricks, MLFlow, Azure ML, OpenShift, or similar platforms
- Experience evaluating business cases for AI use cases, including estimation of value/ROI, complexity, and risk
- Experience in assessing and improving performance, efficacy, and adoption of AI solutions post deployment
- End-to-end delivery of atleast 35 AI projects taken to production, with concrete ownership of planning, execution, and post production monitoring
- Practical experience with AIOps and MLOps concepts and tooling (e.g., Databricks, MLFlow, Azure ML, OpenShift) in real world deployments
- Strong understanding of CI/CD practices for ML, including setting up or working with pipelines using Azure DevOps, Jenkins, etc., for model deployment and updates
- Ability to review and guide solution architectures for AI systems (data pipelines, model training, serving, monitoring)
- Hands on experience with Generative AI technologies – LLMs, RAG, Prompt Engineering – and their application to business use cases is a strong plus
- Broad understanding of machine learning algorithms and techniques, including LLMs/SLMs, supervised/unsupervised learning, and agentic AI, sufficient to challenge and guide technical teams
- Experience defining and monitoring KPIs/SLAs for AI systems (e.g., model performance, latency, drift, adoption, business impact)
- Ability to assess data readiness, technical feasibility, and integration constraints for proposed AI use cases

Immediate Joiners will be preferred only

📌 AI Product Lead / AI Product Owner (Bengaluru)
🏢 Adecco India
📍 Bengaluru