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Strong Fortune-500 brand, Bangalore metro location, and mid-level (5+ years) candidate pool increase competition.
Highly specialized GenAI, LLM deployment, and MLOps skills limit cross-industry transferability.
Explicit 5+ years plus multiple mandatory GenAI, deep learning, and deployment technology requirements.
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Build, deploy, and optimize Large Language Models (LLM), Retrieval-Augmented Generation (RAG), and agent-based AI systems for production environments.
Architect LLM inference and deployment pipelines ensuring efficient, secure, and cost-effective scaling.
Collaborate cross-functionally with data science, research, and product teams while mentoring junior engineers and enforcing engineering best practices including CI/CD and AI ethics.
Bachelor's degree in Information Technology, Computer Science, or related field.
Minimum 5 years of experience in data engineering or software engineering roles.
Strong proficiency in Python, especially with NumPy, Pandas, scikit-learn, and deep learning frameworks such as PyTorch or TensorFlow.
Hands-on experience with LLM frameworks (Hugging Face Transformers, LangChain) and agentic AI frameworks (AutoGen, CrewAI, LangGraph).
Experienced in advanced GenAI technologies, including model optimization (quantization, pruning, distillation) and multimodal AI (text, vision, audio).
Skilled in engineering production-ready AI solutions including microservices, TDD, concurrency, and CI/CD pipelines in cloud environments (AWS, Azure, GCP).
Proficient with data engineering tools, especially Snowflake, and managing vector databases and RAG pipelines for semantic search applications.