Experience:Â 9-12 years
Location: Pune, India (Hybrid)
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. - 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
- 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