Lead AI Engineer

Role Lead AI Engineer Mandatory Skills Python, Multi-LLM system, RAG, AWS Lambda, Amazon API Gateway, Claude models, Bedrock-hosted models (AWS Bedrock, AWS Bedrock Knowledgebase) Primary Skills Python, Multi-LLM system, RAG, AWS Lambda, Claude models, Bedrock-hosted models (AWS Bedrock, AWS Bedrock Knowledgebase) Good to Have AWS Total Experience 8+ years Relevant Experience 7+ years Work Location Kochi / TVM / Remote Qualification Bachelor's Degree Job Purpose We are seeking a hands-on Lead AI Engineer to build, integrate, and operationalize Agentic AI capabilities, predominantly with Gen AI. This is a core engineering role responsible for day-to-day implementation of AI features using AWS-native tooling. Job Description / Duties and Responsibilities AI Engineering Build agentic solutions with conversational agents at the front end and agentic automation for data retrieval at the backend. Build Text-to-SQL AI capability. Build graph databases from SQL as well as unstructured data. Build and optimize RAG pipelines and Graph RAG capabilities. Evaluate LLMs (primarily AWS Bedrock-based, and additionally other cloud and on-prem LLMs) for performance, scalability, and cost. Knowledge of GPU-based LLM installation and management is a plus. Knowledge of MLOps and methodologies for model and agentic deployment is required. Backend Development Develop scalable services using: AWS OpenSearch Service AWS S3 Amazon DynamoDB AWS CloudWatch Deploy via: AWS Lambda Amazon API Gateway Amazon CloudFront Model Optimization Prompt engineering Retrieval tuning Latency optimization Output quality improvement Adhere to the Information Security Management policies and procedures. Job Specification / Skills and Competencies Required Skills Hands-on experience in GenAI application development. RAG implementation. Graph implementation. LLM integration. Strong AWS serverless experience. Experience working with Bedrock-based architectures. Ability to work independently in embedded teams. Experience leading a small team of 2 to 4 members. Customer management and requirements analysis. Ability to solve AI business problems. Nice to Have Experience with healthcare or sensitive data systems. Exposure to AI evaluation frameworks. Multi-model orchestration experience. Bachelor's or Master's degree in Computer Science, or a related field. Strong coding skills in Python and ML libraries such as TensorFlow, PyTorch, or scikit-learn. Experience with data preprocessing, feature engineering, and model lifecycle management. Proficiency in ML pipelines and deployment using MLflow, Docker, Kubernetes, or similar. Familiarity with AWS cloud platform and related AI/ML/LLM services. Strong understanding of statistics, probability, and data modeling.