AI/ML Engineer

Agilisium; Pune District; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Agilisium seeks a Senior GenAI/AI-ML Engineer to design and deploy production-grade Generative AI solutions. You will work on end-to-end AI/ML pipelines, model integration, and scalable services using Python, LangChain, LangGraph, and FastAPI.

The role requires hands-on experience with LLMs, RAG, and cloud deployments across AWS/Azure/GCP, with a focus on enterprise data sources and secure, scalable architectures. Pune-based, on-site opportunity.

Qualifications

• Bachelor's degree in CS, Data Eng, AI/ML, or related field (Master's preferred).
• 3+ years of experience in AI/ML with hands-on Generative AI and LLM-based applications.
• Strong hands-on experience with Generative AI/LLMs, including model integration, evaluation, optimization, and deployment.
• Strong expertise in Python and building scalable AI applications and services.
• Hands-on experience with LangChain and LangGraph for developing LLM-powered applications, workflows, and AI agents.
• Experience with Retrieval-Augmented Generation (RAG) solutions including document ingestion, embeddings, retrieval and response generation.
• Strong hands-on experience with FastAPI for developing and exposing AI/ML services and APIs.
• Experience with LLM APIs and model providers such as OpenAI, Azure OpenAI, Hugging Face, Anthropic, Gemini, etc.
• 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.

Skills

Generative AI

LLMs

Python

LangChain

LangGraph

RAG

Prompt engineering

Education

Bachelor's degree in Computer Science, Data Engineering, AI/ML, or related field

Master's degree preferred

Tools

Docker

Kubernetes

CI/CD

FastAPI

LLM APIs

Job description

We’re looking for a Senior GenAI / AI-ML Engineerwith strong hands-on experience in designing and deploying production-grade Generative AI solutions.

Must-have skills:

• Bachelor’s degree in Computer Science, Data Engineering, AI/ML, or a related field(Master’s preferred).
  
• 3+ years of experiencein 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 Pythonand experience building scalable AI applications and services.
  
• Hands-on experience with LangChainand LangGraphfor 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 FastAPIfor developing and exposing AI/ML services and APIs.
  
• Experience working with LLM APIs and model providerssuch 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 platformssuch 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 workflowsusing 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 expertiseis highly desirable.
  
• Experience integrating GenAI solutions into production-level enterprise applications.