Agentic AI Developer (AWS Bedrock)

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

• Strong 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

• Strong 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.