Artificial intelligence
Engineering professionals in Artificial intelligence
Explore which technical limits actually slow down AI product delivery and increase operating costs. Engineering leaders who've shipped AI systems can show you where infrastructure, model complexity, or data pipelines create real bottlenecks—and which constraints matter most for your situation.
Professionals to explore
01—10Ercan Kamber
LinkedInExperience: Senior Vice President, Product Engineering AI Platforms, Reliability & Agentic AI · Realpage
Experience leading product engineering for AI platforms and agentic AI, including building engineering organizations that turn AI into production systems.
Karthik Gopalratnam
LinkedInExperience: Senior Director Of Engineering · google
Experience as a senior engineering director leading teams building AI agents for enterprise customers across retail, finance, and SMB verticals.
Kelvin Ong
LinkedInExperience: Director of Artificial Intelligence Technology · NVIDIA
Experience designing and optimizing AI deep learning platform architecture and leading cross-functional teams deploying AI solutions across global markets.
Madhur Mayank Sharma
LinkedInExperience: Vice President, AI Product Engineering & Global Head of AI Services & Accelerator · SAP
Experience leading AI product engineering and global AI services delivery at an enterprise software company, including building AI engineering organizations.
Paul Dakessian
LinkedInExperience: Director, AI Software Engineering (CoPilot) · Microsoft
Experience directing AI software engineering for a major AI product, including driving GenAI and LLM integration into production systems.
Shadi Saba
LinkedInExperience: Vice President of Engineering, AI ML · CoreWeave
Experience leading engineering organizations building AI cloud infrastructure for frontier AI workloads, including distributed training and inference systems.
Shashidhar Singhal
LinkedInExperience: Director of AI Engineering · Deutsche Telekom Digital Labs
Experience directing AI engineering for conversational and agentic AI systems, including building multi-agent architectures and managing AI engineering teams.
Siva Sivakanesh
LinkedInExperience: Technical Director, Digital Products & AI · Binnies
Experience directing architecture and delivery of AI and digital platforms including scientific machine learning and agentic AI in regulated engineering environments.
Stefan Serban
LinkedInExperience: Head of Product Engineering & Applied AI · MaintainX
Experience leading engineering teams focused on AI/ML product delivery and applied AI, with prior engineering leadership roles at Upwork and Box.
Sudhindra Venkatesh Kulkarni
LinkedInExperience: Director - AI Engineering · HP
Experience directing AI engineering delivery, including leading innovation and large-scale delivery of AI solutions across a print ecosystem.
Choose the right perspective
Look for candidates who've owned decisions about model serving, compute resources, or system reliability in production. Ask what they chose to do differently after hitting a technical wall. Avoid those who only discuss theoretical problems; focus on people who've had to pick between competing technical solutions.
Questions to take into the conversation
- 01When you had to cut costs or speed up delivery, which technical constraint forced your hand the most?
- 02What would need to change about your infrastructure or model approach to make a real difference to reliability or cost?
- 03Tell me about a time you chose a simpler technical solution over a more sophisticated one—what made that the right call?
About this directory
This is a professional research starting point based on business profile data retrieved on . Titles and companies reflect that source snapshot and may describe past or present roles. Check the linked profiles for current details. Inclusion does not imply Instant Expert membership or availability.
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