Vetted Prompt Engineering Professionals

Akhilesh Patil

Screened

Junior AI/ML Engineer specializing in FinTech and generative AI

Remote, USA2y exp

“Built an end-to-end AI bug triage dashboard that combined React/TypeScript, FastAPI, Postgres, and classical ML to reduce manual engineering triage work by about 40%. Stands out for pragmatic, product-minded AI engineering: choosing interpretable models when they were sufficient, designing human-in-the-loop UX for trust, and separately building an agentic RAG project with vector search, Neo4j knowledge graphs, and reranking.”

“Built and deployed PIKA, an internal multi-agent platform for FDA-regulated software development, owning it from concept through production. The candidate combines strong full-stack engineering with rigorous LLM orchestration, human-in-the-loop controls, and production eval systems, delivering measurable impact: 3x more design issues caught, ~90% fewer false positives, and ~40% efficiency gains on documentation-heavy workflows.”

DAVID STOKER

Screened

Senior Product and Program Leader specializing in technology, AI, and aerospace operations

Kent, WA12y exp

“Product leader with experience spanning Boeing, Amazon, and ScribeAmerica, combining large-scale operational product builds with human-centered AI in healthcare. Most notably led Amazon's Fleet Edge initiative to 35,000 deployed devices and an estimated $88M in savings, then helped shape Speke AI into a multi-platform medical documentation workflow product focused on provider trust, adoption, and real-world usability.”

Jason Main

Screened

Executive product leader specializing in AI, SaaS, and Healthcare IT

Austin, TX20y exp

“Product leader with experience spanning AWS enterprise software commercialization, healthcare workforce platforms, and AI-enabled peer mentoring products. Notable wins include launching a healthcare internal resource pool product that offset declining revenue by 3x+ and helping commercialize Amazon call center software into a product that generated just under $25M in first-year revenue. Strong throughline is customer-led product strategy, cross-functional execution, and human-centered AI that augments rather than replaces people.”

“Built and owned an LLM support copilot at Stripe focused on improving agent ticket resolution. Designed the backend and ML system end to end, using RAG, Redis caching, hybrid vector search, and LoRA fine-tuning to achieve 40% lower latency and 22% higher response accuracy, with continuous quality monitoring via Ragas and related evaluation frameworks.”

“Built a production RAG-based "knowledge copilot" for support/ops using LangChain/LangGraph, implementing the full pipeline (ingestion, chunking, embeddings, vector DB retrieval/rerank, guarded generation with citations) and operating it as monitored microservices with CI/CD. Also designed an event-driven, streaming backend for real-time inventory ordering predictions that reduced stockouts by 25%, and has hands-on incident response experience stabilizing LLM API latency/5xx spikes using Datadog/APM and resilience patterns.”