Back
Tier-1 brand plus seniority and metro context create moderate competition for specialized ML leaders.
Highly domain-specific ML/AI, MLOps, cloud, and healthcare familiarity increases background sensitivity.
Explicit 12+ years plus mandatory LLM, MLOps, Databricks, cloud and Scala create strict hiring filters.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Lead and manage teams delivering enterprise-scale AI/ML and Generative AI solutions with focus on architecture, strategy, and operational excellence.
Drive adoption and integration of emerging AI technologies such as LLMs, Agentic AI, RAG, and Responsible AI practices in cloud-native enterprise platforms.
Collaborate cross-functionally to translate business priorities into scalable, secure, and compliant AI solutions ensuring platform reliability and governance.
12+ years professional experience in AI/ML engineering including experience with Generative AI, LLM-based applications, and big data platform development.
Bachelor's or Master's degree in Computer Science, Information Technology, or equivalent.
Hands-on experience with Python, Scala, Snowflake, SQL/PLSQL, Docker, Kubernetes, Microsoft Azure, and MLOps practices.
Experience with AI/ML model development frameworks (TensorFlow, PyTorch), CI/CD pipelines, Agile environments, and implementing AI governance and compliance controls.
Senior engineering leader with deep expertise in enterprise AI/ML platforms, cloud environments (preferably Azure), and advanced AI technologies such as LLMs and Agentic AI.
Experienced in managing cross-functional teams and driving AI strategy aligned with business objectives in large-scale environments.
Practitioner able to bridge hands-on technical implementation and high-level architecture with governance and operational excellence focus.