Ai Ml Engineer

Agilisium

Pune District

In loco

INR 3.000.000 - 6.000.000

Tempo pieno

14 giorni+

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Descrizione del lavoro

Agilisium in Pune is seeking a senior AI/ML engineer to design and deploy Generative AI and LLM-based applications. You will integrate LangChain, LangGraph, and RAG pipelines with FastAPI services, handling model selection, evaluation, and deployment.

The role requires 5+ years in AI/ML, strong Python, cloud experience, and hands-on work with vector databases, embeddings, and multi-agent workflows. Collaboration with data engineers, researchers, and product teams is essential.

Competenze

  • Bachelor's degree in Computer Science, Data Engineering, AI/ML, or a related field (Master's preferred).
  • 5+ years of experience in AI/ML with hands-on Generative AI and LLM-based applications.

Mansioni

  • Develop and deploy Generative AI/LLM-based applications and services.
  • Integrate LangChain, LangGraph, and RAG pipelines for AI agents and workflows.
  • Build scalable AI solutions with FastAPI and cloud services.
  • Collaborate with cross-functional teams to deliver production-grade AI systems.

Conoscenze

Generative AI
LLMs
Python
LangChain
LangGraph
RAG
FastAPI
MLOps
Cloud platforms
Prompt engineering
Vector databases
SQL/NoSQL
Model deployment
Embeddings
Data ingestion
AI security
Team collaboration

Formazione

Bachelor's degree in CS/AI/related field
Master's preferred

Strumenti

Docker
Kubernetes
CI/CD
Hugging Face

Descrizione del lavoro

Role & responsibilities

Generative AI | LLM | Python | LangChain | LangGraph | RAG | FastAPI

Must Have:

MCP | AI Agents | Vector Databases | LLM Fine-tuning | Cloud | MLOps | Life Sciences

Must-have skills:
  • Bachelors degree in Computer Science, Data Engineering, AI/ML, or a related field (Master's preferred).
  • 5+ years of experience in AI/ML, with significant hands-on experience in Generative AI and LLM-based applications.
  • Strong hands-on experience with Generative AI / Large Language Models (LLMs), including model integration, evaluation, optimization, and deployment.
  • Strong expertise in Python and experience building scalable AI applications and services.
  • Hands-on experience with LangChain and LangGraph for developing LLM-powered applications, workflows, and AI agents.
  • Strong experience building Retrieval-Augmented Generation (RAG) solutions, including document ingestion, chunking, embeddings, retrieval, reranking, context management, and response generation.
  • Strong hands-on experience with FastAPI for developing and exposing AI/ML services and APIs.
  • Experience working with LLM APIs and model providers such as OpenAI, Azure OpenAI, Hugging Face, Anthropic, Gemini, or equivalent.
  • Good understanding of prompt engineering, embeddings, vector search, and LLM evaluation.
  • Experience integrating GenAI solutions with SQL/NoSQL databases, vector databases, and enterprise data sources.
  • Strong understanding of cloud platforms such as AWS, Azure, or GCP and their AI/ML services.
  • Understanding of MLOps, model lifecycle management, deployment, monitoring, and productionization of AI solutions.
  • Strong problem-solving, communication, and collaboration skills, with the ability to work with cross-functional teams.
Preferred Skills
  • Model Context Protocol (MCP) experience, including building or integrating MCP servers/tools with LLM applications or AI agents.
  • Experience developing AI Agents / Agentic AI workflows using LangGraph or similar frameworks.
  • Experience with multi-agent systems, tool calling, function calling, and structured outputs.
  • Experience with vector databases such as Pinecone, Weaviate, Qdrant, Chroma, Milvus, or FAISS.
  • Experience with LLM fine-tuning, LoRA/PEFT, or model optimization.
  • Experience with Docker, Kubernetes, CI/CD, and cloud-native deployments.
  • Strong understanding of AI security, data governance, responsible AI, and enterprise GenAI architecture.
  • Life Sciences / Pharma / Healthcare domain expertise is highly desirable.
  • Experience integrating GenAI solutions into production-level enterprise applications.
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