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Mid-level GenAI lead in a metro with sought-after skills and moderate-brand, creating medium competition.
Highly specialized GenAI, transformer, and deployment expertise limits cross-industry transferability.
Explicit 5–6 years, deep-learning and GenAI technical stack requirements increase strictness.
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Lead development of advanced generative AI applications including multimodal and agentic systems using frameworks like LangChain and LlamaIndex.
Design and deploy scalable AI workflows encompassing reasoning, planning, tool-use, and knowledge graph integration, ensuring safety and hallucination control.
Collaborate cross-functionally to translate business needs into AI solutions and mentor junior engineers while driving best practices and R&D efforts.
5-6 years of software development experience including machine learning model deployment in production.
2+ years working with deep learning, generative AI, or transformer architectures with experience beyond basic RAG systems.
Strong programming skills in Python with API development and backend experience using Flask/FASTAPI/Django.
Hands-on experience deploying AI systems on cloud platforms like AWS, Azure, or GCP and working with big data technologies (Spark, Hadoop, MongoDB).
Experienced lead engineer skilled in building complex GenAI systems involving multimodal inputs, agentic workflows, and knowledge graph-assisted retrieval.
Proficient in end-to-end model development, fine-tuning (LoRA/QLoRA), and deployment with an emphasis on production scalability and monitoring.
Operates effectively in cross-functional, enterprise-grade environments requiring collaboration, documentation, and mentoring with hybrid onsite work in Pune.