Vetted Prompt Engineering Professionals

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.”

“Early-stage full-stack engineer who built Dokai's core web spreadsheet product and key AI features with just a two-engineer team. They combine strong product ownership with practical LLM integration experience, including reducing onboarding from a week to five minutes and solving difficult reliability and memory issues in production.”

“CMU engineer with hands-on experience building full-stack AI products across internships and academic projects, including a Microsoft real-time multimodal assistant and a Cursor-like coding agent. Stands out for combining low-latency systems engineering with strong product instincts, shipping AI tools that improved latency by 35%, cut grading time from five days to under 10 minutes, and reduced user resubmissions by 45%.”

veera krishna chaitanya Arepalli

Screened

Mid-level Full-Stack Engineer specializing in AdTech and FinTech

Menlo Park, CA5y exp

“Meta product engineer with strong ad-tech experience who owned monetization and optimization features across Instagram Boost on mobile and web. They combine product analysis, experimentation, and full-stack execution, citing $9.8M/year from an upsell feature and $43K/day from feeding IG-to-WhatsApp lead signals into ad targeting. Also built an internal LLM-powered analytics agent to automate adoption-rate analysis for product teams.”

“Technical co-founder of Aldata AI for nearly three years, building an AI platform that ingests 100+ engineering data sources to analyze team behavior and correlate it with business outcomes. Combines hands-on architecture leadership, fast startup execution rhythms, and revenue-driven product prioritization, with prior experience in larger corporate environments like Chase.”