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Hexaware Technologies

Gen AI Developer Specialist

Posted 2 Days Ago
Remote
Hiring Remotely in United States
Entry level
Remote
Hiring Remotely in United States
Entry level
Design, develop, and maintain enterprise AI applications, including conversational assistants, copilots, autonomous agents, RAG solutions, and workflow automation. Build scalable APIs and microservices integrating foundation models and enterprise systems. Apply prompt and context engineering, memory management, observability, governance, and performance optimization. Collaborate with cross-functional teams to identify automation opportunities and participate in Agile development, code reviews, CI/CD, and DevSecOps.
The summary above was generated by AI
  • 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.

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