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Tier-1 brand, popular Product Manager title, mid-level experience, and metro location increase applicant competition.
AI product skills are transferable, though hands-on LLM and automotive preference add moderate industry specificity.
Explicit years, mandatory PM and hands-on LLM experience, and technical stack create strict shortlisting filters.
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Own the product vision, strategy, and roadmap for AI/ML-powered products, managing end-to-end lifecycle including discovery, development, launch, and iteration.
Lead multiple concurrent AI/ML product workstreams using agile methods and tools like Jira and Confluence, ensuring clear communication with leadership and stakeholders.
Hands-on contribute to prototyping, fine-tuning, and iterating on LLMs and other ML models, collaborating closely with engineering and data science on architecture and MLOps decisions.
Bachelor's degree in Engineering (B.E./B.Tech) in Computer Science, IT, Electronics, or related discipline.
5 to 7 years total professional experience, with at least 3 years in Product Management, preferably in AI/ML or data-driven products.
Proven hands-on experience building, fine-tuning, or deploying Large Language Models (LLMs), supported by portfolio or project examples.
Practical knowledge of Python and ML/AI frameworks (PyTorch, TensorFlow, Hugging Face) or LLM tooling (LangChain, LlamaIndex, vector DBs).
Experienced in managing multiple AI/ML product workstreams simultaneously in fast-paced environments using agile/scrum methodologies and relevant collaboration tools.
Technically credible with demonstrated ability to work hands-on with AI/ML model development alongside engineers and data scientists, bridging technical and business domains.
Preferably has domain experience in automotive, mobility, or manufacturing industries and familiarity with responsible AI practices and cloud AI platforms (Azure ML, AWS SageMaker, GCP Vertex AI).