• Hands-on experience with LLM integration (GPT, Gemini) and prompt engineering
• Proficiency with LangGraph and LangSmith for building AI workflows and agents
• Experience with agent builder platforms, multi-agent systems, and agent orchestration
• Familiarity with Model Context Protocol (MCP), MCP Tools, and A2A communication
• Knowledge of vector databases (PostgreSQL/PGVector), embeddings, and Drift
• Experience with Snowflake SQL and its AI capabilities (Cortex AI, Snowpark ML)
• Design, develop, and deploy AI-powered applications leveraging our enterprise AI stack from concept to production
• Build and execute proof-of-concepts (POCs) using Large Language Models (LLMs), agent frameworks, and modern AI orchestration tools
• Develop intelligent agents and multi-agent systems using LangGraph and agent builder platforms
• Implement Model Context Protocol (MCP) integrations, MCP Tools, and agent-to-agent (A2A) communication patterns
• Leverage enterprise AI capabilities including vector stores, embeddings, and RAG architectures
• Manage code through CI/CD pipelines and maintain proper observability of AI applications
• Contribute to our internal agent registry and maintain integration standards
Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field
At Zensar, we’re “experience-led everything”. We are committed to conceptualizing, designing, engineering, marketing, and managing digital solutions and experiences for over 130 leading enterprises. We are a company driven by a bold purpose: Together, we shape experiences for better futures. Whether for our clients, our people, or the world around us, this belief powers everything we do. At the heart of our culture is ONE with Client - a set of four core values that reflect who we are and how we work: One Zensar, Nurturing, Empowering, and Client Focus.