AI /ML Engineer

We are seeking a highly skilled AI Engineer with expertise in Generative AI, AWS Bedrock, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Vector Databases. The ideal candidate will be responsible for designing, developing, and deploying enterprise-grade AI solutions leveraging AWS AI services and modern data architectures.

This role requires hands-on experience in building scalable AI applications, integrating foundation models, implementing RAG frameworks, and deploying production-ready GenAI solutions.

Key Responsibilities

• Design and develop Generative AI solutions using AWS Bedrock and foundation models.

• Build and optimize RAG (Retrieval-Augmented Generation) pipelines using vector databases.

• Develop AI-powered applications including chatbots, virtual assistants, document intelligence, and agentic AI solutions.

• Integrate LLMs with enterprise applications, APIs, and data platforms.

• Design and maintain vector search architectures using Pinecone, Weaviate, OpenSearch, ChromaDB, or similar platforms.

• Develop scalable data ingestion, embedding, indexing, and retrieval pipelines.

• Implement prompt engineering, model evaluation, fine-tuning, and guardrails.

• Collaborate with Data Engineers, Solution Architects, and Product teams to deliver AI-driven solutions.

• Ensure security, scalability, observability, and governance of AI applications.

• Monitor model performance and continuously improve AI solution accuracy and efficiency.

Generative AI

• Strong understanding of LLMs and Generative AI concepts.

• Experience with RAG architecture and Agentic AI frameworks.

• Prompt Engineering and Model Evaluation.

• Fine-tuning and model optimization techniques.

AWS Cloud

• AWS Bedrock

• Amazon SageMaker

• AWS Lambda

• API Gateway

• ECS/EKS

• S3

• DynamoDB

• CloudWatch

• IAM

Vector Databases

• Pinecone

• Weaviate

• ChromaDB

• OpenSearch Vector Engine

• FAISS

• Milvus

Programming

• Python (Mandatory)

• LangChain

• LangGraph

• LlamaIndex

• FastAPI

• REST APIs

Data & Integration

• SQL

• NoSQL Databases

• ETL Pipelines

• Data Modeling

• API Integration

DevOps & MLOps

• Docker

• Kubernetes

• CI/CD Pipelines

• GitHub Actions

• Terraform

• Model Monitoring and Governance

Required Skills for candidate to Qualifiy:-

• Experience with, Financial Services, or Life Sciences domains.

• Experience deploying AI solutions in production environments.

• AWS Certified Machine Learning Engineer or AWS Solutions Architect certification.

• Experience with multi-agent frameworks and autonomous AI systems.

Education

• Bachelor''s or Master''s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.

Nice to Have

• Knowledge of Anthropic Claude, Amazon Nova, Llama, Mistral, and OpenAI models.

• Experience with Knowledge Graphs.

• Experience with Databricks and Snowflake.

• Experience with Agentic AI and AI Orchestration frameworks.