AI/ML Engineer – Agentic AI

Overview

Experience Required

Job Overview

Key Responsibilities

• Design, develop, and deploy AI/ML solutions for real-world business use cases
• Build and optimize
• Agentic AI systems
• using LLMs, autonomous workflows, and multi-agent architectures
• Develop machine learning models for prediction, classification, recommendation, NLP, and automation tasks
• Work with orchestration frameworks such as LangChain, CrewAI, AutoGen, LangGraph, or similar technologies
• Integrate AI agents with APIs, databases, enterprise systems, and third-party tools
• Fine-tune, evaluate, and optimize Large Language Models (LLMs)
• Develop Retrieval-Augmented Generation (RAG) pipelines and vector search implementations
• Collaborate with data engineers, software developers, and product teams to deliver scalable AI solutions
• Perform prompt engineering, model experimentation, and performance optimization
• Ensure AI solutions are production-ready, scalable, secure, and cost-efficient
• Monitor model performance, drift, and continuous improvement processes
• Stay updated with emerging AI, Generative AI, and Agentic AI trends and technologies

Required Skills & Expertise

• Strong hands-on experience in
• Machine Learning, Generative AI, and Agentic AI development
• Proficiency in Python and AI/ML development frameworks
• Experience with:
• + LangChain, LangGraph, CrewAI, AutoGen, or similar frameworks
• + OpenAI, Anthropic, Gemini, or open-source LLMs
• + RAG architectures and Vector Databases
• + Prompt Engineering & AI workflow automation
• Solid understanding of:
• + NLP concepts
• + ML algorithms and model evaluation
• + Deep Learning fundamentals
• + AI model deployment and inference optimization
• Experience with ML libraries/frameworks such as:
• + PyTorch
• + TensorFlow
• + Scikit-learn

+ Hugging Face Transformers

• Experience with cloud platforms such as Azure, AWS, or GCP is preferred
• Familiarity with Docker, APIs, CI/CD, and MLOps practices
• Strong problem-solving and analytical skills

Preferred Qualifications

• Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, or related field
• Experience working on enterprise AI automation or AI assistant platforms is highly preferred
• Exposure to AI governance, evaluation frameworks, and AI observability tools is a plus