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Tier-1 brand, metro location, and mid-level (5+ years) generalist title amplify competition.
GenAI engineering skills are broadly transferable, though healthcare domain knowledge mildly matters.
Explicit 5+ years and mandatory GenAI/ML frameworks, production and MLOps experience make screening strict.
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Build and deploy scalable Generative AI systems including LLM, RAG, and agent-based architectures.
Architect and optimize LLM inference and deployment pipelines for efficiency and cost-effectiveness.
Collaborate cross-functionally with data science, research, and product teams while mentoring junior engineers and enforcing engineering best practices.
Bachelor's degree in Information Technology, Computer Science or related field.
Minimum 5 years of experience in data engineering or software engineering roles.
Strong expertise in Python, deep learning frameworks (PyTorch/TensorFlow), and LLM frameworks (Hugging Face Transformers, LangChain).
Experience with LLM serving, agentic AI frameworks, RAG pipelines, semantic search, and software engineering practices such as microservices and TDD.
Experienced senior software engineer with demonstrated ability to prototype and productionize state-of-the-art GenAI solutions rapidly.
Deep knowledge of generative AI, including practical skills with cloud AI deployment and data platforms like Snowflake.
Strong collaborator able to work cross-functionally and mentor team members, with emphasis on clean, reproducible, and secure AI development.