Lead AI Engineer

Experion Technologies · Kochi

Source and collection record

Last observed by our collector: 8 October 2026 at 11:24 pm IST. This is not a manual review or a confirmation from the employer.

Employer requisition: lead-ai-engineer

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Collected role description

Job Purpose We are seeking a hands-on Lead AI Engineer to build, integrate, and operationalize Agenitc AI capabilities, pre dominantly 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 AI Engineering Build agentic solution with conversational agents at front end & agentic automation for data retrieval at the backend. Build Text to SQL AI capability Build Graph Database from SQL as well as unstructured data Build and optimize RAG pipelines, Graph RAG capabilities etc Evaluate LLMs (primarily AWS Bedrock based, additionally other Cloud and on-prem LLMs) for performance, scaling & cost perspectives Knowledge on GPU based LLM installation/management is a plus Knowledge of MLOps and methodologies of model/agentic deployment is requisite 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 Job Specification / Skills 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 Leading a small of 2 - 4 members. Customer Management, Requirements analysis Solution of 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 cloud platform AWS and related AI/ML, LLM services. Strong understanding of statistics, probability, and data modeling.

Collected experience requirement

7+ Years