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Tier-1 brand, metro location, and a visible ML/Data role create high applicant competition.
Specialized LLM and MLOps skills moderately restrict portability, but ML experience remains somewhat transferable.
Explicit 7+ years and many mandatory ML/LLM, vector DB, cloud, and MLOps skills make filters strict.
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Lead development of scalable backend AI platforms focusing on Large Language Models, Retrieval-Augmented Generation, and Agentic workflows.
Build and deploy production-scale GenAI pipelines and optimize LLMs through fine-tuning and prompt engineering.
Develop high-performance APIs and oversee data ingestion, MLOps, and CI/CD for AI services, including mentoring junior developers.
7+ years in software development, with 1-2 years dedicated to Generative AI or LLM integration.
Expert-level Python (5-8+ years) including asyncio and OOP.
Experience with AI frameworks (Hugging Face, PyTorch, TensorFlow) and GenAI libraries (LangGraph, CrewAI).
Bachelor's or Master's degree (or equivalent) in Computer Science, Engineering or related STEM field.
Experienced in architecting and deploying scalable AI systems with cloud platforms (AWS, Azure, GCP).
Proficient in vector databases (Pinecone, Weaviate, FAISS), data engineering (Pandas, NumPy, SQL/NoSQL), and DevOps (Docker, Kubernetes, CI/CD).
Capable of leading technical teams, providing mentorship, and conducting rigorous code reviews in AI-focused software projects.