Vetted Prompt Engineering Professionals

“Deloitte consultant who led cross-functional teams delivering a Snowflake/AWS data ingestion, warehousing, and analytics platform, with a strong track record of executive alignment and risk mitigation. Built reusable business-development accelerators (including an end-to-end Appian app and a Java integration-config tool) credited with helping secure $75M+ in contracts, and has high-confidentiality experience consulting for DoD and FDA.”

“CIO-level technology leader (most recently at Sovos) who owned the full tech roadmap across product, infrastructure, and corporate IT, scaling engineering across 14 countries with an architectural review board and standardized security/observability. Hands-on in high-severity incidents (ransomware) while managing executive/client communications, and drove a reported 40% product-velocity lift by adopting AI code assistants and agentic AI (Devin) alongside Kubernetes + Bottlerocket for secure scalability.”

Vatsal Gabani

Screened ReferencesStrong rec.

Mid Software Engineer specializing in backend systems and AI-enabled platforms

California, USA4y exp

“Full-stack engineer with hands-on ownership of a support ticket intelligence platform, spanning React/TypeScript frontend work and backend API, PostgreSQL, Redis, and Docker-based deployment. They stand out for driving practical architecture and performance improvements in production, including moving heavy processing async and cutting response times from about 300ms to 150ms while improving reliability.”

“Engineering leader and player-coach with a long tenure leading 5 teams/17 engineers, combining organizational leadership with hands-on SQL, architecture, and production incident work. Particularly notable for shipping AI-powered lead engagement systems like an intelligent voice agent, while also driving operational improvements such as release cadence standardization, team restructures, database migrations, and major rules-engine performance gains.”

Venu Dave

Screened ReferencesStrong rec.

Junior Software Development Engineer specializing in backend data platforms and LLM applications

New York, NY3y exp

“Amazon internship experience building and shipping an end-to-end NL-to-SQL system: ingested/normalized metadata across 60+ internal tables, added rigorous multi-layer validation for LLM-generated SQL, and served it via a FastAPI backend for engineers—driving 90%+ faster dataset discovery and ~70% lower effort to access data. Also built an early-stage RAG-based healthcare assistant, iterating on chunking, embeddings, and retrieval to improve answer quality post-launch.”

Andrew Fares

Screened ReferencesStrong rec.

Mid-level Data Engineer specializing in AI, GenAI, and cloud data platforms

Seattle, WA4y exp

“Built production AI systems inside AWS finance/procurement, including an LLM-based supplier quote classification and price-vetting workflow that drove $5M in savings over 3 months. Combines GenAI evaluation expertise, internal platform design, and reusable Python data-quality tooling with strong cross-functional execution across finance, accounting, and hardware engineering.”

“Product and consumer growth professional from a B2C app background, focused on improving retention/activation and driving revenue through customer/product data. Experienced in maintaining BI layers and dashboards and running KPI-driven analysis across returns/refunds operations (NPS/CSAT, TAT, repeat complaints). Familiar with core F2P monetization mechanics and how to evaluate IAP offers via A/B testing; has shipped/managed products on mobile and web.”

“Director of Engineering at Proofpoint for 8 years, leading architecture and integration of Java microservices within a detection platform. Demonstrates pragmatic delivery leadership—incurring short-term cost to meet launch deadlines, then systematically paying down technical debt and optimizing AWS spend—plus a disciplined, long-horizon approach to backward-compatible API/schema evolution across many dependent services.”

“ML/LLM engineer who has built and productionized a large multimodal LLM pipeline end-to-end—fine-tuning a 20B+ parameter model with distributed/FSDP training and deploying on Kubernetes via Triton for ~5x throughput. Strong focus on reliability and safety (monitoring with SHAP, guardrails, A/B testing) with reported ~22% relevance lift and reduced harmful/incorrect outputs, plus experience orchestrating ETL/retraining workflows with Airflow across S3/Snowflake/RDS.”

“Built and deployed a production LLM-powered clinical support assistant at BJC HealthCare (RAG + transformer) to answer patient questions, summarize clinical notes, and support appointment workflows. Implemented PHI-safe data pipelines (Spark/Hadoop/Kafka) with automated scrubbing, dataset versioning, and audit logs, and runs the system on Docker/Kubernetes with Pinecone vector search while partnering closely with clinical operations staff.”

Osvaldo Calles

Screened

Senior Software Engineer specializing in developer tools, cloud automation, and generative AI

Redmond, WA13y exp

“Built and deployed a production chatbot on osvaldocalles.com and iterated through real-world LLM engineering issues: model quota/cost tradeoffs (migrating to Nova Pro), RAG accuracy via semantic chunking, AWS IAM/guardrail/security pitfalls, and Lambda/API Gateway streaming constraints (prefers JS for streaming layer). Experienced with agent orchestration using Strands SDK (AWS-focused) and LangGraph (Vercel/container deployments), plus evaluation pipelines using LLM-as-evaluator, dashboards, and staged model rollouts.”

Rahil Khan

Screened

Executive technology leader specializing in digital transformation, AI, 5G, and telecom platforms

Frisco, TX26y exp

“Founder of a cloud-based TV sharing startup who has already raised angel and Series A funding, then pitched larger VCs in New York and Silicon Valley using an MVP and live demos. Demonstrates practical knowledge of the VC and accelerator landscape, stage-appropriate fundraising, and capital-efficient startup building.”

Jared Hoffen

Screened

Senior AI Engineer specializing in LLM agents, RAG, and ML infrastructure

Las Vegas, USA12y exp

“Production-focused AI/ML engineer who has owned LLM agent and RAG systems end-to-end, from experimentation through deployment, monitoring, and iterative optimization. Stands out for building evaluation and observability layers around GenAI systems and delivering measurable gains in task success, regression detection speed, and token efficiency in production.”

Jeremiah Medina

Screened

Senior AI/ML Engineer specializing in LLMs, RAG, and cloud-native MLOps

Orlando, FL11y exp

“Built and owned a real-time clinical AI assistant at Andor Health, taking it from prototype through deployment, monitoring, and iterative improvement. Brings strong healthcare-focused GenAI experience across RAG, hybrid retrieval, LoRA fine-tuning, and production Python services, with measurable gains in accuracy, speed, and reliability.”

“Product manager with 5+ years spanning JPMorgan Chase and Airbnb, combining fintech, marketplace, and platform experience. Stands out for driving measurable growth— including 50,000 new active users via onboarding experimentation— and for leading ambiguous 0-to-1 internal automation work in a regulated compliance environment.”

“Product manager with 7-8 years of experience spanning e-commerce and internal customer support platforms, including 2.5 years owning a Walmart product used to service customer contacts. Particularly strong at combining data, user research, and AI/LLM capabilities to design support workflows and 0-to-1 agent-assist experiences in ambiguous environments.”

“Strategic enterprise Customer Success leader from Atlassian Cloud managing a >$10M ARR, ~33k-user account end-to-end, driving measurable adoption (+12%), services expansion (+30%), and strong satisfaction (4.5/5). Experienced leading cross-functional deployments of AI agents (Rovo) and Forge-based integrations, and translating enterprise governance needs (e.g., RBAC at scale) into roadmap-shaping product requirements.”

“IAM/platform engineer with experience at DocuSign and Siemens who ships production-grade systems end-to-end: built a secure AWS serverless internal employee-profile API (OAuth2/Cognito/WAF) that cut data retrieval from weeks to near-instant and sustained ~2,800 RPS at ~75 ms. Also delivered production AI workflows, including a GPT-4o + Playwright crypto-scam detection agent and an NLP ticket-routing system improved to ~86.7% accuracy with strong monitoring and incident mitigation practices.”

John Bralich

Screened

Senior Machine Learning Scientist specializing in generative AI and applied NLP

Juno Beach, FL9y exp

“ML/AI tech lead who shipped a production LLM workflow at GoDaddy for personalized marketing content, using rich customer context and human-plus-LLM evaluation to drive a statistically significant increase in customers creating posts with GoDaddy tools. Also has experience translating embedding research into a production government RFP search engine, with hands-on optimization of retrieval latency, model size, and deployment reliability.”

“AI/ML engineer with experience spanning Accenture healthcare NLP systems, academic research, and Apple on-device LLM integration. Stands out for owning regulated production pipelines end-to-end—from HIPAA-compliant clinical NLP and EHR integrations to incident prevention, experiment tracking, and optimized on-device inference with LLaMA 3.”

“Meta engineer who emphasizes AI-native development workflows, using Claude Code heavily to ship UI and performance fixes quickly. Notable examples include a location-aware ad relevance feature that increased CTR and revenue, and a vehicle insights chatbot whose UX improved through metric-driven prompt tuning.”

“Engineer with experience at Reddit working on high-scale backend and infrastructure problems, including API redesign for products serving 150M+ daily active users. They also built a production AI agent for automated bug triage with 97% accuracy and substantial time savings, and have hands-on full-stack/AI side-project experience using React, TypeScript, Supabase, and LLMs.”

“Unity/C# gameplay engineer with strong systems architecture depth who has reworked core gameplay ability frameworks, shipped across mobile and standalone VR, and solved multiplayer synchronization issues with server-authoritative netcode. Also brings an unusual crossover into AI tooling, having owned an AI-powered debugging assistant at Arm and integrated LLM workflows into CI/development pipelines.”