📋 Description

• Design, build, deploy, and improve production-grade AI agents in enterprise client environments
• Combine AI engineering, software engineering, context engineering, and client-facing delivery
• Translate business problems into agentic solutions from discovery to deployment and improvement
• Collaborate with client teams to integrate agents with enterprise systems and tools
• Ensure agents are reliable, secure, and production-ready
• Own outcomes from initial discovery through adoption in production environments

🎯 Requirements

• 6–15 years in AI Engineering, ML, Software Eng, or related field with hands-on production AI
• Strong Python with API/AI service development (FastAPI or similar)
• Hands-on with LLM-powered agentic apps; multi-step workflows, tool calls, state management
• Experience with LangGraph, LangChain, Google ADK, Semantic Kernel, AutoGen, or equivalents
• Hands-on MCP integration with enterprise tools, APIs, databases, apps
• Context engineering expertise: context APIs, memory/state, RAG, dynamic retrieval

🎁 Benefits

• Competitive salary and dynamic career growth
• Idea Tanks for innovation and experimentation
• Growth chats and a collaborative environment
• Snack Zone and recognition programs
• Company-sponsored certifications in AI, Data Science, Cloud, Analytics