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Known brand, mid-level GenAI role in a metro hybrid setting increases applicant competition.
High specialization in GenAI, transformers, and production ML reduces cross-industry transferability.
Explicit 5-6 year minimum plus mandatory deep learning, deployment, and GenAI skill requirements.
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Lead design and development of generative AI applications including multimodal, agentic AI systems, and knowledge-graph augmented solutions.
Deploy and scale AI/ML models as APIs and microservices on cloud platforms (AWS/Azure/GCP), ensuring monitoring, cost-efficiency, and reliability.
Collaborate cross-functionally to translate business needs into AI solutions; mentor junior engineers and standardize AI workflows and best practices.
5-6 years of software development experience with production ML model deployment.
2+ years experience with deep learning, transformers, generative AI beyond simple RAG, including fine-tuning and multimodal models.
Strong programming skills in Python and SQL; backend frameworks Flask, FastAPI, or Django.
Experience with cloud deployment (AWS/Azure/GCP), big data tools (Spark, Hadoop, MongoDB), and developing scalable AI APIs/microservices.
Experienced in building complex generative AI pipelines involving LLMs, agent frameworks, multimodal applications, and knowledge graph integration.
Demonstrates operational ownership of end-to-end AI solution development including deployment, CI/CD, monitoring, and performance optimization in enterprise environments.
Comfortable working in hybrid onsite (minimum 2 days in Pune office) settings with strong collaboration across engineering, data science, and product teams.