AI LeadDeveloper

Required Skills:

Position: AI Lead/Developer Location: Bangalore/Chennai - Hybrid Engagement Mode: Full Time Shift Timing: 9.00AM to 6.00PM IST About the role: We are modernizing our data and analytics ecosystem by embedding AI and Generative AI across core insurance platforms (Policy Claims Billing and Enterprise systems). We are hiring a Lead AI Engineer to build and scale production-grade AI solutions on AWS. This role is hands-on and focused on delivering real systems while helping shape the foundation of our emerging AI platform. This is not a pure research or modeling role. It is an engineering role focused on building deploying and operating AI systems in a regulated enterprise environment. Key Responsibilities: Build AI Systems (Core Responsibility) Design and implement end-to-end AI/ML solutions including LLM-based applications Build RAG pipelines using vector databases and enterprise data sources Build machine learning models that automate their training validation monitoring and retraining Develop APIs and services to operationalize AI capabilities across the organization Develop Data AI Pipelines Build ingestion for multimodal content and transformation pipelines for structured and unstructured data Integrate AI workflows with enterprise systems (policy claims billing etc.) Ensure data quality traceability reliability and governance in all AI pipelines Operationalize Models (MLOps) Implement CI/CD for AI/ML workflows Deploy monitor and maintain models in production Manage model versioning performance monitoring and retraining processes Build on AWS Develop solutions using: Amazon SageMaker AWS Lambda S3 Glue EKS and related services Contribute to evolving use of AWS Bedrock Apply Responsible AI Practices Implement guardrails for LLM-based systems (grounding validation safety) Ensure secure handling of sensitive data (PII financial etc.) Build systems aligned with enterprise governance and compliance standards Lead by Doing Provide technical guidance and mentorship to engineers Contribute to engineering standards and reusable patterns Partner with architects and business teams to deliver high-impact use cases Must-Have Skills & Responsibilities: Required 10 years in software data engineering 5 years AI/ML engineering Hands-on experience building production AI/ML systems Experience with RAG pipelines LLMs or NLP-based systems Experience with AWS Bedrock or similar GenAI platforms Experience with data pipelines and distributed systems Experience deploying and operating systems in AWS Working knowledge of MLOps practices (CI/CD monitoring versioning) Preferred Experience with vector databases (Pinecone Weaviate etc.) Experience in regulated industries (insurance finance healthcare) Exposure to microservices and containerized environments (Docker Kubernetes)

Required Education:

Any Degree