Design, develop, and deploy advanced Agentic AI systems that autonomously plan, reason, orchestrate tools, and execute multi‑step tasks. Provide hands‑on expertise across LLMs, agent frameworks, orchestration layers, retrieval systems, and tool integrations. Contribute to the development of production‑grade agentic applications while collaborating with architects, ML engineers, and product teams to deliver scalable, reliable, safe, and cost‑efficient autonomous AI systems. Knowledge & Skills • Experience with LLM ecosystems including OpenAI, Azure OpenAI, Anthropic, Llama, and other transformer-based models; familiarity with prompt engineering and agent behaviour patterns. • Proficiency in Python and/or TypeScript with hands-on experience in agent frameworks such as LangChain, LangGraph, Semantic Kernel, or custom orchestration engines. • Knowledge of RAG design patterns, retrieval pipelines, vector databases (Pinecone, Chroma, FAISS, Weaviate), and memory systems for autonomous agents. • Understanding of AI safety, guardrails, hallucination mitigation, security controls, versioning, telemetry, and monitoring for production AI systems. Mandatory Experience • 4–6 years of software development experience with at least 2 years hands-on building LLM/AI applications, autonomous agents, or orchestration-based systems. • Hands-on experience integrating LLMs with APIs, structured data sources, vector stores, and cloud-native services across AWS/Azure/GCP. • Experience building robust, modular, scalable AI applications following clean architecture principles, best coding practices, and automated testing. • Debugging and optimization skills for LLM-driven pipelines, including prompt refinement, latency optimization, caching, and observability.