About The Role

Design, develop, and maintain AI-powered enterprise applications using React, TypeScript, JavaScript, Python, and Microservices Architecture .
Leverage GitHub Copilot, Claude Code, Amazon Q Developer, and other AI coding assistants to convert business requirements and user stories into production-ready code and pull requests.
Architect and develop AI-enabled solutions using LLMs, GenAI services, and Agentic AI frameworks .
Build scalable backend APIs and microservices integrating AI services with enterprise systems.
Design and implement Retrieval Augmented Generation (RAG) solutions using vector databases and enterprise knowledge repositories.
Develop conversational AI applications, copilots, virtual assistants, and intelligent workflow automation solutions.
Implement Prompt Engineering and Context Engineering techniques to improve AI output quality, consistency, and performance.
Build autonomous and semi-autonomous AI agents capable of orchestrating multi-step business processes.
Design memory management strategies, including:
Short-term Memory
Long-term Memory
Context Windows
Token Optimization
Integrate AI services using:
Amazon Bedrock
Claude
OpenAI
Other Foundation Model Platforms
Develop event-driven architectures leveraging Kafka and cloud-native messaging services.
Collaborate with Product Owners, Architects, Business Analysts, and Development teams to identify AI automation opportunities.
Implement AI governance, observability, monitoring, and performance optimization practices.
Participate in Agile development, code reviews, CI/CD automation, and DevSecOps processes .