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Pune metro and popular AI role increase competition, but specialized OpenAI expertise and senior requirement reduce applicant density.
High because role demands deep OpenAI/LLM engineering, production RAG systems, and domain-specific AI expertise.
High because JD mandates 8+ years, 3+ years OpenAI experience, and numerous mandatory technical requirements.
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Lead design, development, and deployment of enterprise-grade OpenAI-powered AI solutions including agentic RAG systems, chatbots, and automation workflows.
Architect scalable multi-agent AI pipelines using OpenAI Agents SDK, LangGraph, LangChain with robust tool and memory management.
Mentor junior engineers and establish AI engineering best practices within Zensar's AI platform; collaborate with stakeholders to translate business needs into AI architectures.
8+ years of AI/ML engineering experience with at least 3 years hands-on OpenAI platform expertise.
Expert proficiency with OpenAI API features including GPT-4o, Assistants API, Function Calling, Fine-Tuning, Embeddings.
Strong Python skills including async programming and scalable backend development; proficiency with ML frameworks like PyTorch, TensorFlow, scikit-learn.
Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or equivalent practical experience.
Experienced architect of production-grade agentic RAG systems, conversational AI, and multi-agent orchestration pipelines using OpenAI toolkits and LLM orchestration frameworks (LangChain, LangGraph, OpenAI Agents SDK).
Skilled in scalable system design and MLOps practices including CI/CD for ML, model benchmarking with OpenAI Evals, and responsible AI implementation.
Familiar with enterprise AI deployments involving Azure OpenAI Service and data engineering platforms (Snowflake, dbt, Informatica IICS); capable of communicating technical trade-offs to technical and executive audiences.