We are seeking a highly skilled Agentic AI Developer with strong expertise in AWS Bedrock, LLMs, RAG Architectures, Multi-Agent Frameworks, Python FastAPI, Kafka, Java Spring Boot, Snowflake, and SQL. The ideal candidate will be responsible for designing, developing, and deploying enterprise-scale Agentic AI solutions using AWS Bedrock while building scalable and intelligent AI-driven workflows.

This role requires hands-on experience with Generative AI, autonomous AI agents, prompt engineering, knowledge bases, and cloud-native AI architectures.

Key Responsibilities

Agentic AI & Generative AI Development

- Design and implement Agentic AI solutions using AWS Bedrock.
- Develop intelligent AI agents using:

- AWS Bedrock Agents

- Knowledge Bases

- Guardrails
- Build autonomous AI workflows capable of reasoning, planning, and tool orchestration.
- Implement Retrieval-Augmented Generation (RAG) architectures for enterprise use cases.
- Develop multi-agent orchestration frameworks and AI-powered business workflows.

AI Engineering & Prompt Design
- Design advanced prompt engineering strategies including:

- Chain of Thought (CoT)

- Tree of Thought (ToT)

- ReAct Framework
- Optimize LLM interactions for accuracy, efficiency, and reliability.
- Implement AI evaluation and monitoring frameworks.

Backend Development
- Develop REST APIs and AI services using:

- Python

- FastAPI

- Java Spring Boot
- Build scalable backend services supporting AI agents and orchestration frameworks.
- Integrate AI services with enterprise applications and APIs.

Cloud & AWS Development
- Design and build serverless architectures using:

- AWS Bedrock

- AWS Lambda

- AWS Step Functions

- Amazon EventBridge




- Develop cloud-native AI solutions leveraging AWS services.
- Implement monitoring, scalability, and security best practices.

Data Integration & Orchestration
- Work with:

- Snowflake

- SQL Databases

- Kafka Event Streaming
- Build enterprise knowledge repositories and retrieval pipelines.
- Integrate vector databases and retrieval frameworks to support RAG implementations.

Collaboration & Delivery
- Collaborate with architects, product teams, data engineers, and stakeholders.
- Participate in Agile delivery cycles and sprint planning.
- Support design reviews, solution architecture discussions, and AI innovation initiatives.
- Deliver enterprise-grade AI solutions with focus on scalability, performance, and governance.

Required Skills

- Hands-on experience with:

- AWS Bedrock

- Agentic AI

- Generative AI

- LLMs

- Experience implementing
- Retrieval-Augmented Generation (RAG)
- Multi-Agent Systems

- Knowledge Bases

- AI Agent Workflows

- Strong development expertise in

- Python

- FastAPI

- Java

- Spring Boot

- Experience with

- Kafka

- Snowflake

- SQL
- Robust understanding of AI orchestration frameworks.
- Experience building cloud-native applications on AWS.
- Familiarity with serverless architectures and event-driven systems.

Preferred Skills

- Core Python expertise.
- GraphQL.
- LangChain.
- Bedrock AgentCore.
- Vector Databases.
- AI Evaluation Frameworks.
- Prompt Engineering Techniques.
- MLOps and GenAI Governance.

Desired Candidate Profile

- Robust analytical and problem-solving skills.
- Excellent communication and collaboration abilities.
- Passion for AI innovation and emerging technologies.
- Experience working in Agile environments.
- Ability to develop scalable and production-ready AI solutions.

📌 Agentic AI Developer (AWS Bedrock) (Bengaluru)
🏢 Tata Consultancy Services
📍 Bengaluru