Experience: 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:
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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:
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Build knowledge repositories from text, audio, and video sources using embeddings, transcription, and summarization pipelines.
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Enable multi-modal knowledge extraction for downstream agent decision-making and summarization.
Proof of Concept (POC) & Presales:
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Rapidly prototype solutions to showcase feasibility and demonstrate agentic AI architectures to clients.
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Collaborate with sales and solution engineering teams to support presales activities, including architecture walkthroughs, technical demos, and proposal inputs.
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Provide thought leadership on agentic AI best practices and tool integrations.
Integration & Tooling:
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Work with APIs, vector DBs (Pinecone, Weaviate, FAISS, etc.), relational databases, and NoSQL stores (MongoDB).
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Enable smooth data flow across enterprise systems to empower AI agents.
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Ensure secure, scalable, and efficient deployment of AI pipelines in enterprise contexts.
Required Skills & Experience:
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Proven experience in building agentic flows using LangChain, LangGraph, n8n.
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Solid knowledge of MCP server setup and integration with agent workflows.
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Experience in RAG architecture, vector databases, and multi-database interactions (SQL, MongoDB).
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Practical exposure to web crawling and MCP integrations (e.g., Tavily, custom MCP agents).
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Proficiency in building knowledge bases from structured/unstructured content (text, audio, video).
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Ability to deliver rapid POCs and guide customers on architecture & integration strategy.
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Familiarity with cloud platforms (Azure, AWS, GCP) for AI/ML deployment.
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Strong problem-solving skills and a self-starter mindset.
Preferred Qualifications:
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Experience with enterprise AI solution design and customer-facing roles (presales, consulting).
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Understanding of AI security, compliance, and governance considerations.
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Knowledge of data pipelines and ETL for AI use cases.
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Contributions to open-source AI/agentic frameworks.
Soft Skills:
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Excellent communication and presentation skills for customer interactions.
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Ability to work independently with minimal supervision.
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Strong collaboration skills with cross-functional teams (sales, product, delivery).
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Curiosity and continuous learning mindset to stay ahead in AI/ML innovations.
Role Type:
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Hybrid (Pune)
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Involves customer interaction, presales support, and solution delivery
