Lead end-to-end delivery of enterprise GenAI/ML products, set engineering standards for production readiness, and elevate team capability through strong technical leadership and mentorship
Job Summary
Lead end-to-end delivery of enterprise GenAI/ML products, set engineering standards for production readiness, and elevate team capability through strong technical leadership and mentorship.
Build and scale agentic GenAI applications that solve multi-step workflows on cloud platforms such as AWS and Azure.
Stay current with the latest advancements in Generative AI, cloud technologies, and ML/LLMOps practices, and proactively translate relevant insights into team and platform adoption.
Matching Summary
Lead end-to-end delivery of enterprise GenAI/ML products, set engineering standards for production readiness, and elevate team capability through strong technical leadership and mentorship.
Skills & Requirements
Must-have
GenAI and Machine Learning Engineering
production-grade full-stack GenAI solutions
backend systems, data, and AI/ML engineering
enterprise GenAI/ML products
agentic GenAI applications
LLMOps and lifecycle governance
Python and PySpark
Nice-to-have
partner to Business leaders
cutting edge of artificial intelligence
novel project execution
Responsible AI, security, and compliance
platform thinking
DataBricks, AWS bedrock, Microsoft Copilot Studio and Azure ML
Key Requirements
Over 7+ years of experience in software development
hands-on experience with software development toolkits
DevOps automation like Kubernetes, Airflow, Jenkins, Jira, Confluence and Git