Position Title : AI/ML Engineer – Agentic AI
Experience Required: 4–6 Years (Should be open to Travel)
Employment Type : Full-Time
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
