Software Engineer

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