Machine Learning Engineer (Agentic AI & LLMs)
Position Overview
We are seeking a hands-on Machine Learning Engineer with strong expertise in LLMs, Agentic AI frameworks, and MCP-based architectures . The ideal candidate will have practical experience designing and deploying agentic flows that integrate RAG pipelines, knowledge bases, and multi-database interactions. This role requires a self-starter who can not only deliver robust solutions but also actively contribute to presales discussions, customer enablement, and quick POCs to demonstrate value.
Key Responsibilities
- Agentic AI & LLM Development
- Design, implement, and optimize agentic workflows using LangChain, LangGraph, n8n , and related orchestration tools.
- Setup and manage MCP servers and integrate them into agent-driven pipelines.
- Develop RAG (Retrieval-Augmented Generation) solutions leveraging vector databases, relational databases, and MongoDB.
- Implement web crawling and external MCP services (e.g., Tavily) to enhance agent capabilities.
- Knowledge Base Engineering
- Build knowledge repositories from text, audio, and video sources using embeddings, transcription, and summarization pipelines.
- Enable multi-modal knowledge extraction for downstream agent decision-making and summarization.
- Proof of Concept (POC) & Presales
- Rapidly prototype solutions to showcase feasibility and demonstrate agentic AI architectures to clients.
- Collaborate with sales and solution engineering teams to support presales activities , including architecture walkthroughs, technical demos, and proposal inputs.
- Provide thought leadership on agentic AI best practices and tool integrations.
- Integration & Tooling
- Work with APIs, vector DBs (Pinecone, Weaviate, FAISS, etc.), relational databases, and NoSQL stores (MongoDB).
- Enable smooth data flow across enterprise systems to empower AI agents.
- Ensure secure, scalable, and efficient deployment of AI pipelines in enterprise contexts.
Required Skills & Experience
Strong hands-on expertise with LLMs (OpenAI, Anthropic, or open-source models) and Agentic AI frameworks.Proven experience in building agentic flows using LangChain, LangGraph, n8n .Solid knowledge of MCP server setup and integration with agent workflows.Experience in RAG architecture , vector databases, and multi-database interactions (SQL, MongoDB).Practical exposure to web crawling and MCP integrations (e.g., Tavily, custom MCP agents).Proficiency in building knowledge bases from structured / unstructured content (text, audio, video).Ability to deliver rapid POCs and guide customers on architecture & integration strategy .Familiarity with cloud platforms (Azure, AWS, GCP) for AI / ML deployment.Strong problem-solving skills and a self-starter mindset .Preferred Qualifications
Experience with enterprise AI solution design and customer-facing roles (presales, consulting).Understanding of AI security, compliance, and governance considerations.Knowledge of data pipelines and ETL for AI use cases .Contributions to open-source AI / agentic frameworks .Soft Skills
Excellent communication and presentation skills for customer interactions.Ability to work independently with minimal supervision.Strong collaboration skills with cross-functional teams (sales, product, delivery).Curiosity and continuous learning mindset to stay ahead in AI / ML innovations.Role Type
Hybrid (Pune)Involves customer interaction, presales support, and solution delivery