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Strong employer brand, metro location, and mid-level generalist AI role drive high applicant competition.
Specialized ML/LLM and agentic orchestration skills create strong domain bias and lower cross-industry transferability.
Explicit 4–6 years plus many mandatory ML/LLM, vector DB and agentic framework skills increases strictness.
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Design, develop, deploy, and maintain AI and machine learning solutions that address business problems, including traditional ML, Generative AI, and Retrieval-Augmented Generation (RAG) architectures.
Architect and deploy autonomous multi-agent AI systems capable of complex reasoning, decision making, task routing, and external tool/API interaction.
Develop AI solutions integrating large language models (OpenAI, Google Gemini, Claude) with orchestration frameworks (LangChain, LlamaIndex) and vector databases, including prompt engineering for autonomous workflows.
4-6 years of overall experience with at least 2-3 years in AI or machine learning engineering or related field.
Bachelor's degree in Computer Science or related field with minimum 3 years relevant experience.
Proficient in Python (mandatory); knowledge of Java and Angular/React for full stack integration is required.
Hands-on experience with AI/ML frameworks (Hugging Face, LangChain, LlamaIndex, OpenAI API, TensorFlow, Keras, PyTorch) and vector databases (Pinecone, ChromaDB).
Experienced in end-to-end AI/ML model lifecycle including concept to production deployment in complex environments.
Skilled in building autonomous agentic AI systems and advanced AI orchestration using frameworks like LangGraph, CrewAI, AutoGen.
Capable of working with cloud infrastructure, containerization, CI/CD pipelines, and MLOps practices for scalable AI solution deployment.