Senior Analyst

• *Role Summary**

================

We are looking for a hands\-on Senior AI/ML Engineer to design, build, and deploy production\-grade Agentic AI and Generative AI solutions.

• *Key Responsibilities**

========================

• **Agentic system design:** Architect and build single\- and multi\-agent systems with planning, tool use, memory, reflection, and human\-in\-the\-loop controls for complex business workflows.
• **LLM implementation:** Integrate and optimize LLMs (Anthropic Claude, OpenAI GPT, Google Gemini, Llama, Mistral) via APIs
• **RAG pipelines:** Design retrieval\-augmented generation solutions, including chunking, embeddings, hybrid search, re\-ranking, and vector database management.
• **Tool and integration layer:** Implement function/tool calling and Model Context Protocol (MCP) servers to connect agents with enterprise systems, APIs, and data sources.
• **Prompt and context engineering:** Develop robust prompts, system instructions, structured outputs, and context\-management strategies (including prompt caching) to maximize quality and cost efficiency.
• **Evaluation and observability:** Build evaluation frameworks (golden datasets, LLM\-as\-judge, regression testing) and monitor agents for accuracy, latency, cost, hallucination, and drift.
• **Leadership:** Mentor junior engineers, conduct code and design reviews, contribute to reusable accelerators, and support pre\-sales technical discussions and PoCs.

• *Required Skills**

===================

• 5\-8 years of experience in AI/ML or software engineering, with at least 1 or 2 years building LLM/GenAI applications in production.
• Strong Python proficiency; experience with FastAPI/Flask, async programming, and clean, testable code.
• Hands\-on experience with the Anthropic Claude API/SDK (messages, tool use, extended thinking, prompt caching, vision, batch processing) and at least one other LLM provider.
• Proven experience building AI agents using frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, Claude Agent SDK.
• Working knowledge of MCP, tool/function calling, and multi\-agent orchestration patterns (planner\-executor, supervisor, router, reflection).
• Solid understanding of embeddings, vector databases (Pinecone, FAISS, Chroma) and search relevance tuning.
• Experience with fine\-tuning open\-source models, and inference serving Ollama.
• Collaboration with data engineers, product owners, architects, and client teams.