AI Lead/Developer
Indexed description
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
- 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)
- Deploy, monitor, and maintain models in production
- Manage model versioning, performance monitoring, and retraining processes
- Develop solutions using: Amazon SageMaker, AWS Lambda, S3, Glue, EKS, and related services
- Contribute to evolving use of AWS Bedrock
- 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
- 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.
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)
- Experience with vector databases (Pinecone, Weaviate, etc.)
- Experience in regulated industries (insurance, finance, healthcare)
- Exposure to microservices and containerized environments (Docker, Kubernetes)
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