- 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.

- / 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

-- Robust 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

-- Bachelors or Masters 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.

- Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Lead AI Engineer (Kochi)
🏢 Experion
📍 Kochi