Machine Learning Engineer (Agentic AI & LLMs)

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