Ai Ml Engineer

2 days ago

Mumbai, Maharashtra, India Iitjobs Inc. Full time ₹ 12,00,000 - ₹ 36,00,000 per year

About the Role:

AI Engineer

We are seeking a highly skilled AI Engineer with 5+ years of hands-on experience in AI/ML, Generative AI, and Agentic AI systems. The ideal candidate will have a deep understanding of AI agent frameworks,

Model Context Protocol (MCP), Databricks, and cloud-native MLOps workflows. This role involves building, deploying, and optimizing intelligent systems from LLM-powered applications to autonomous multi-agent architectures.

Key Responsibilities:

  • Design, develop, and deploy machine learning and generative AI models in production environments.
  • Build and integrate agentic AI systems intelligent agents capable of reasoning, planning, and multi-step decision-making.
  • Develop and maintain data pipelines and MLOps workflows using Databricks, MLflow, and cloud-native tools.
  • Integrate LLMs and AI agents with external APIs, databases, and tools using agent frameworks (LangChain, AutoGen, CrewAI, Semantic Kernel, LangGraph).
  • Implement and manage Model Context Protocol (MCP) connections between agents and enterprise systems.
  • Optimize AI workloads in AWS, Azure, or GCP environments with scalable, secure infrastructure.
  • Collaborate with cross-functional teams (data, cloud, and product) to deliver AI-driven solutions.
  • Ensure AI system security, observability, explain ability, and compliance with governance standards.

Ideal Candidate Profile:

  • AI / ML & Data Science -Strong foundation in machine learning, deep learning, and data science concepts.
  • Expertise in Python with ML libraries: PyTorch, TensorFlow, scikit-learn, pandas, NumPy.
  • Knowledge of model evaluation, feature engineering, and transfer learning.

  • Experience with vector databases (FAISS, Pinecone, ChromaDB).

  • Generative AI & NLP - Hands-on experience with LLMs, prompt engineering, RAG (Retrieval- Augmented Generation), and fine-tuning.

  • Familiarity with LangChain, LlamaIndex, or similar orchestration frameworks.

  • Implementation of text generation, summarization, classification, and document Q&A systems.
  • Agentic AI, Agent Frameworks & MCP -Deep understanding of agentic AI systems autonomous, multi-step, tool-using architectures.
  • Practical experience building AI agents using frameworks such as LangChain, AutoGen, CrewAI, LangGraph, or Semantic Kernel.
  • Experience designing multi-agent collaboration systems and task orchestration.
  • Hands-on experience implementing or integrating Model Context Protocol (MCP) for tool invocation, context sharing, and agent-to-system communication.
  • Strong awareness of safety, governance, auditability, and agent evaluation frameworks.
  • Databricks, MLOps & Data Engineering - Strong experience with Databricks (Spark, Delta Lake, MLflow, feature store).

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