Vetted Large Language Models (LLMs) Professionals

“Software development manager who led development of the open-source AI agents framework Strands (for Amazon Bedrock), which launched mid-year and is used as a primary agent-development framework at Amazon and externally. Owned the Strands SDK end-to-end, drove adoption through stakeholder management and agile execution, and led a JavaScript-to-TypeScript migration to improve type safety and maintainability.”

“Senior engineering/technology leader with experience driving board-backed, multi-year platform transformations in retail commerce (American Eagle) and scaling ML/product delivery platforms at Amazon Alexa. Known for data-driven build-vs-buy decisions, org scaling (6→80), and measurable outcomes including 98.5%→99.9% uptime, 234 experiments generating ~$200M revenue lift, and increasing delivery velocity from 1.5 to 30 features/week while transitioning to DNN/large-model architectures.”

Kevin Wang

Screened

Senior Software Engineer specializing in cloud infrastructure and distributed systems

Adams, MA8y exp

“Amazon engineer focused on productionizing LLM-powered developer workflows, including code assistance, debugging automation, and internal AI tooling. Stands out for combining hands-on ML systems work with strong platform engineering, including an orchestration engine that reportedly saved about $10K/day and reduced a manual workflow from 12 hours to under a second.”

Christopher Sipola

Screened

Senior Machine Learning Engineer specializing in LLMs and recommendation systems

New York, NY11y exp

“ML/GenAI engineer who owned major parts of Spotify’s AI DJ from offline experimentation through deployment, monitoring, and iteration. They combine recommender systems, RAG, real-time feedback loops, and LLM safety/orchestration to ship consumer-facing personalization features that drove double-digit engagement and deeper listening sessions.”

Alok Kumar

Screened

Director-level Product Management leader specializing in cybersecurity, cloud, and AI governance

Atlanta, GA24y exp

“Senior product leader with substantial end-to-end build experience across Microsoft, Amazon, NCR, and a current AI startup. Particularly notable for creating a machine-readable compliance platform at Microsoft, shipping AI-enabled support workflows, and combining enterprise-scale product rigor with a human-centered view of personalized AI.”

“Senior product leader with experience spanning Amazon Audible, Capital One, and At-Bay, combining growth, AI, and workflow platform expertise. Notable for leading Audible's Channels build/rebuild, reshaping Capital One's Eno around real service outcomes, and redesigning an underwriting platform with flexible search and agentic alerts. Brings a strong human-centered view of AI informed by both consumer fintech and insurance automation.”

“Strategy and operations leader with experience spanning Anheuser-Busch and McMaster-Carr, combining large-scale cost ownership, frontline operations leadership, and sourcing strategy. Particularly compelling for operationally intensive roles: they’ve managed a 150-person service organization, owned a ~$750M cost base, built strategy in ambiguous environments, and independently drove an LLM automation pilot that reached 97% accuracy and saved 3 FTEs.”

“Senior Microsoft engineering leader who has led globally distributed orgs of up to 250 engineers while staying deeply technical in large-scale platform architecture, reliability, and AI systems. Notable work includes modernizing Teams infrastructure serving massive global scale and incubating an internal AI pair-programmer/knowledge-graph platform over 650M lines of code, plus helping launch foundational Copilot search and retrieval APIs.”