Machine Learning Engineer (Agentic AI & LLMs)

Experience

Location

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.

Agentic AI & LLM Development

• Design, implement, and optimize agentic workflows using LangChain, LangGraph, n8n, and related orchestration
  tools.
  


• 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.

• 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.

• 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.

• 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.

• Hybrid (Pune)


• Involves customer interaction, presales support, and solution delivery