AI/ML Engineer – Agentic AI

Overview

Job Overview

• We are seeking a highly skilled AI/ML Engineer with hands-on experience in building intelligent AI systems, machine learning models, and Agentic AI solutions.
• The ideal candidate will have strong expertise in designing, developing, and deploying AI-powered applications leveraging LLMs, autonomous agents, orchestration frameworks, and modern ML techniques.
• The role requires a strong engineering mindset, practical AI implementation experience, and the ability to work across the full AI/ML lifecycle from experimentation to production deployment.
• **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.
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