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

Bachelors 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.

/ 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.
• 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 AWS cloud platform and related AI/ML/LLM services.
• Strong understanding of statistics, probability, and data modeling.