Description

Key Responsibilities

• Agentic AI Development:
  • Design and develop LLM-based AI agents capable of reasoning, planning, and task execution
  • Build and manage multi-agent orchestration workflows
  • Enable agents to interact with enterprise systems (APIs, databases, tools)
• Java & Backend Engineering:
  • Develop scalable backend applications using Java, Spring Boot, and Microservices
  • Build REST APIs to support AI-driven workflows and integrations
  • Ensure performance, scalability, and maintainability of services
• GCP & GenAI Implementation:
  • Develop AI solutions using Vertex AI, Gemini, BigQuery, Cloud Run, and Pub/Sub
  • Work with Vertex AI Agent Builder and Google ADK for agent development
• LLM, RAG & Context Engineering:
  • Implement Retrieval-Augmented Generation (RAG) pipelines
  • Build context-aware systems using vector search and embeddings
  • Optimize prompts and workflows for performance and cost
• MLOps & Deployment:
  • Deploy and monitor AI models and agents in production
  • Implement CI/CD pipelines, logging, and observability
  • Ensure reliability, safety, and guardrails for AI systems

Required Skills and Qualifications

• Experience:
  • 3–7 years of software development experience
  • Strong hands-on experience in Python
  • 2 years experience building and deploying real-world agents in a production environment
  • Strong hands-on experience in Java backend development (4 years exp)
  • Hands-on experience in developing AI/ML or Generative AI projects
• Core Technical Skills:
  • Hands-on experience on Google ADK, MCP servers, agent to agent communication, agent orchestration
  • Java (4+ years), Spring Boot, Microservices
  • REST APIs and distributed systems design
  • Hands-on experience on Python, LLMs, GenAI, and agent-based systems
  • Hands-on experience with GCP services (Vertex AI preferred)

Key Skills

Education

Any Graduate