Vetted Prompt Engineering Professionals

Joseph Villanueva

Screened

Senior Software Engineer specializing in full-stack SaaS and Healthcare IT

San Francisco, CA8y exp

“Product-minded software engineer from Gusto who has shipped internal AI agent capabilities and end-to-end user-facing features across frontend and backend. Stands out for making pragmatic architecture tradeoffs—moving from OpenAI prototypes to deterministic systems when accuracy, latency, and uptime mattered—while still improving LLM workflow quality and reducing tool-calling errors by 15%.”

“Built AI-powered natural language search and summarization features for internal financial platforms at JPMorgan, with a strong focus on trust, compliance, auditability, and failure handling. Stands out for treating AI as one component in a larger enterprise system rather than a magic layer, and for combining hands-on LLM integration experience with thoughtful agent architecture and validation design.”

Kiran Kumar

Screened

Mid-level Software Engineer specializing in Java microservices and GenAI automation

USA4y exp

“Software engineer (4+ years) with hands-on production GenAI experience: built an AI incident triage assistant that summarizes production logs for on-call engineers and iterated it using real incident metrics (time-to-signal, triage duration). Also shipped a RAG-based customer support knowledge assistant using embeddings + vector retrieval with strong guardrails (relevance thresholds/abstain, sanitization, auditing) and a formal eval loop (500-query gold set) that drove measurable retrieval improvements.”

Mos Fard

Screened

Senior Distributed Systems Architect specializing in backend platforms and FinTech

Scottsdale, AZ12y exp

“Full-stack engineer who built an AI-powered visual product discovery feature end to end across web, mobile, backend, and ML integration. Particularly strong in TypeScript-first monorepo architecture, serverless AWS microservices, and productionizing computer vision/LLM pipelines with monitoring, prompt refinement, and human-in-the-loop quality controls.”

“Architecture leader from Disney who managed system, AI, and data architects while staying hands-on in solution design. Has experience building LLM-based video advertising products, designing Kafka-based real-time data architectures, and using MVP/POC approaches to align product and executive stakeholders.”

“Frontend engineer with strong ownership of high-scale, real-time support product experiences at Zendesk. Particularly compelling for teams building complex browser UIs: they’ve solved ordering/correctness issues in asynchronous messaging, improved agent UX with measurable behavioral signals, led a GraphQL subscription migration that tripled connection capacity, and delivered WCAG-compliant accessibility for AI-assisted features.”

“Built and shipped open-source LLM/RAG systems, including a generative AI assistant grounded on ~30,000 scraped university web pages, improving response accuracy ~30% by moving from TF-IDF-only retrieval to a hybrid sentence-transformer approach with fallback controls. Also partnered with non-technical leadership at Securi.ai to deliver real-time predictive analytics dashboards (Elasticsearch + Jira/ServiceNow) that reduced project overhead by 18%.”

“Backend-focused Python engineer who built an end-to-end personalized chatbot service integrating Amazon Redshift context retrieval with Amazon Bedrock, including prompt construction and production-grade reliability controls. Strong platform experience deploying containerized services to Kubernetes with GitOps/ArgoCD, plus hands-on Kafka streaming and phased infrastructure migration execution.”

“AI/ML practitioner who built an Indian Sign Language recognition system (MediaPipe hand keypoints + CNN/RNN) as an accessibility-focused teaching aid, iterating closely with advocacy groups and educators and reaching 92% accuracy. Also has production-scale data migration experience at Saasgenie, using Kubernetes pod parallelization to migrate 1M+ ITSM records with a 5x throughput gain under API rate limits.”

“LLM/agentic systems builder at Verizon who deployed a LangGraph-orchestrated multi-agent ticket-automation platform with RAG (FAISS) to replace brittle rule-based bots. Improved routing correctness by ~30–40%, hit ~300ms latency targets via model routing, and reduced ops workload by ~60% through tight iteration with non-technical stakeholders and strong testing/observability practices.”

“Built a production-style PyTorch LSTM system that generates structured piano compositions from 1200+ MIDI files, then significantly improved long-range musical coherence by implementing Bahdanau attention based on research literature. Also has internship experience using Docker Compose for containerized backend workloads and has independently used Ray to scale ML experiments across multiple GPUs, including dealing with GPU scheduling/memory oversubscription issues.”

“Software engineer with experience at Striim and Amazon who ships end-to-end production systems across UI, backend, ML, and operations. Built a real-time PII detection capability for a streaming data platform by integrating Python ML inference into a Java monolith via gRPC sidecars, achieving ~3M events/hour throughput and ~93% accuracy, and helped drive enterprise adoption (Fiserv, CVS). Also modernized internal Amazon tooling for multi-region scale with modularization and fully automated deployments.”

“Backend/LLM engineer who built a production-critical Amazon Bedrock + RAG correction and compliance layer for employee communications, integrating tightly with existing Spring Boot/AWS microservices to reduce manual review while keeping outputs explainable and auditable. Also designed an event-driven system processing 10M+ events/day (SQS/Lambda/DynamoDB/Elasticsearch) and handled on-call incidents with strong observability and reliability patterns (idempotency, retries, hotspot mitigation).”

Akshaya Rajagopalan

Screened

Mid-level Full-Stack Software Engineer specializing in cloud SaaS and accessible web apps

Waterloo, Canada6y exp

“Frontend engineer who leads end-to-end delivery of complex workflow-driven React + TypeScript products on top of Rails/GraphQL backends, with a strong emphasis on typed API contracts, scalable architecture, and automated quality gates. Shipped major features (e.g., inventory reservation at Jobber) using feature-flagged rollouts, close QA collaboration, and performance-focused iteration.”

Deepika Gotla

Screened

Senior Technical Support Engineer specializing in Azure Cloud & Generative AI

Bellevue, WA7y exp

“Microsoft cloud/infra engineer with 5+ years supporting enterprise Azure environments, specializing in security-focused networking (private endpoints, DNS) and production troubleshooting across Azure Front Door/App Gateway WAF/AKS. Has implemented posture improvements via Defender for Cloud, Azure Policy, and RBAC tightening, and also designs secure AWS agent/scanner integrations and modern EKS/GitHub Actions/Secrets Manager observability-enabled SDK rollouts.”

Shriya Bannikop

Screened

Mid-level Software Engineer specializing in cloud platforms, data engineering, and distributed systems

Seattle, WA5y exp

“Full-stack engineer who built and owned an AI-assisted job-matching dashboard in Next.js App Router/TypeScript, keeping LLM logic server-side and improving performance via deduplication, caching/revalidation, and streaming (35% fewer duplicate LLM calls; 40% faster first render). Also has strong data/backend chops: designed Postgres models and optimized queries at million-record scale (1.8s to 120ms) and built durable AWS multi-region telemetry workflows with idempotency, retries, and monitoring.”

Vidhi Upadhyay

Screened

Senior Software Engineer specializing in AI/ML, computer vision, and cloud-native systems

Remote8y exp

“Independently built a production-grade, containerized enterprise agentic AI platform (stateful orchestration + RAG) focused on real-world reliability—guardrails, citation-based outputs, reranking, query rewriting, and evaluation harnesses to reduce hallucinations. Hands-on with OpenAI SDK, CrewAI, and LangGraph, and has delivered AI solutions for non-technical NGO stakeholders via demos and practical POCs.”

Parth Gupta

Screened

Junior Robotics & Computer Vision Engineer specializing in perception and autonomy

Ames, IA2y exp

“Robotics engineer with capstone experience building an autonomous food-assembly robot arm, owning perception/deep learning (SAM2-based segmentation) and a model-based RL manipulation policy for deformable food items while also serving as project manager. As a robotics engineering intern at Salin247, optimized an autonomous farm vehicle perception stack to hit 20 FPS by cutting latency from 200ms+ to ~40ms using GPU acceleration (CUDA OpenCV, CuPy) and multiprocessing, and built ROS 2 nodes for real-time perception and streaming.”

Abraham Musa

Screened

Senior Solutions Architect specializing in cloud AI infrastructure and security

Union City, NJ9y exp

“Cloud-native architect focused primarily on AWS, with experience designing Kubernetes and AI/ML infrastructure for customers rather than owning day-to-day operations. Particularly interesting for AI platform roles: they described using Amazon Bedrock to analyze Terraform and automatically generate compliant IaC templates and runbooks for new multi-cloud AI environments.”

“Built and shipped production LLM agents that automate document processing and decision workflows, with a strong focus on reliability, guardrails, and measurable business impact. Stands out for combining RAG, tool calling, evals/monitoring, and ERP integration to deliver 30-35% manual effort reduction and higher throughput without additional headcount.”

“Applied ML/LLM engineer currently building AppleCare’s production chat recommender, owning the full lifecycle from transcript cleaning and fine-tuning through distributed deployment, monitoring, and iterative improvement. Their work delivered >10% copy-count improvement, 5% lower modification rate, 60% cost reduction, and $1.1M profitability in 2025, and they also created a reasoning-data generation approach that enabled a reasoning model and a judge model that cut eval time by over 99%.”

“Product-minded software engineer with experience shipping AI-powered financial insights (spend forecasting, cashflow, credit optimization) and building real-time analytics systems using React/TypeScript and FastAPI. Has designed microservices with RabbitMQ/gRPC and strong observability (Prometheus/Grafana/OpenTelemetry), and also built an internal Figma plugin adopted by designers that reduced export time by 50%.”

“Full-stack engineer from early-stage startups who has owned AI products end to end, from B2B document intelligence platforms on AWS to an HVAC voice assistant and a GCP-based RAG research system. Stands out for combining hands-on backend/infra depth with team leadership in lean environments, and for shipping scalable AI systems that contributed to roughly 1 million yuan in sponsorship.”