Vetted Large Language Models (LLMs) Professionals

Jingfei Xu

Screened

Intern/Junior Software Engineer specializing in AI/ML and cloud-based systems

Mountain View, CA0y exp

“Embedded/robotics software engineer with Hyundai Motors experience who owned an AI-driven perception validation pipeline using a Transformer-based approach to generate stable synthetic in-cabin audio for autonomy/ASR testing, cutting downstream testing time by 50%+. Has hands-on ROS integration (IMU sensor streaming, inference, control nodes), MQTT-based distributed messaging, and cloud/container deployment experience (Docker, Node/Express, AWS, CI/CD).”

“Built and shipped a production LLM-powered medical scribe that generates structured clinical visit summaries using RAG, strict JSON schemas, and post-generation validation to reduce hallucinations. Experienced in making LLM workflows deterministic and observable (structured logging/metrics/tracing) and in evaluation-driven iteration with metrics like schema pass rate and edit rate; collaborated closely with clinicians and policy stakeholders at Scale AI to drive adoption.”

“DevOps/SRE focused on cloud-based distributed systems, with strong hands-on Kubernetes production experience (microservices deployments, Helm, probes, resource tuning, CI/CD and Docker build standardization). Demonstrated end-to-end troubleshooting across application, infrastructure, and networking layers—e.g., isolating degraded storage via node disk I/O metrics and restoring performance by draining the node and replacing the volume. Builds Python automation for operational reliability, including scheduled Kubernetes secrets rotation integrated with an external secret manager.”

Sergey Pustovit

Screened

Director-level Data Platform & Analytics Engineering Leader specializing in distributed systems

Irvine, CA31y exp

“Entrepreneurially minded builder focused on proving architecture concepts via minimal demo prototypes for marketing. Has hands-on experience improving an A/B experimentation framework by interviewing stakeholders, identifying system limits and bottlenecks, and defining success criteria to scale experimentation and speed up analysis.”

“Serial entrepreneur who has created several companies, brought them to market, raised as much as $15M, and achieved exits before moving on to new ideas. Combines an academic and institutional background spanning Harvard, MIT, Mass General Brigham, and the Department of War with two decades of consulting experience, and is especially motivated by building impactful technology.”

David Gross

Screened

Entry AI Software Engineer specializing in LLM workflows and ML pipelines

Redmond, WA2y exp

“Built an autonomous-agent document indexing concept in a hackathon with Microsoft and The Seattle Times, architecting an Azure-based system (Azure AI Foundry, Cosmos DB, Azure indexing, Copilot Studio) and coordinating closely with the customer team. Also created and pitched a sports matchmaking app (Ludicon), combining user studies, feature implementation, and technical support on sales/investor calls.”

Pankaj Goyal

Screened

Director-level Engineering Leader specializing in FinTech, IAM, and AI/ML platforms

SF Bay Area, CA22y exp

“Player-coach backend leader at PostLo who led a major backend architecture upgrade to enable AI-driven features by separating transactional systems from AI workloads (vector embeddings/image validation) and adding async processing for heavy jobs. Also owned production reliability improvements (query/index optimization, workload isolation, monitoring and load testing) and translated an ambiguous retention goal into a shipped cashback rewards feature with auditable transactions.”

“Technology/engineering leader with experience at Real Messenger, Wolters Kluwer, and Accenture AI, spanning roadmap definition through execution and org scaling. Has operated at the executive level (fundraising, investor relations, SPAC merger activities, media presentations) while driving architecture decisions validated by PoC/testing/production success metrics.”