Vetted Full-Stack Development Professionals

Mike Henniger

Screened ReferencesStrong rec.

Staff Software Engineer specializing in scalable backend and full-stack web systems

Burlingame, CA32y exp

“Frontend-leaning full-stack product engineer with IMVU experience who designed both user-facing flows and the production telemetry behind them. Most notably, they built a JavaScript crash detection system using signature-based aggregation and Redis that helped reduce crash volume from millions per day to tens of thousands, and they pair that reliability mindset with reusable UI architecture and onboarding design for consumer social products.”

“Frontend-leaning full-stack engineer who described owning an artist search and detail experience across UI, backend integrations, and data modeling. They show practical strength in scalable React architecture, TypeScript safety, and performance tuning, with a product-minded approach to shipping 0→1 features quickly and iterating after launch.”

“Backend/AI engineer who has built a rule-service platform on AWS and evolved it into an agentic RAG system using LangChain, ReAct, tool calling, and LLM-as-judge review. Notable for combining heavy AI-assisted development with production safeguards like manual CR, CloudWatch monitoring, fallback strategies, benchmark testing, and user-feedback-driven model improvement.”

Rashi Agrawal

Screened

Mid-Level Full-Stack Software Engineer specializing in distributed systems and cloud-native microservices

Novi, MI4y exp

“Backend engineer (4 years) who built an end-to-end Python backend for a patent-pending in-car massager/heater system, including GraphQL data modeling and Bluetooth integration with an ESP32 microcontroller (reverse engineered a niche protocol). Also has strong platform experience: on-prem Kubernetes/CI-CD (Jenkins/GitLab, exploring ArgoCD GitOps), Terraform-based infra workflows, a RabbitMQ messaging library used across microservices, and an on-prem migration of ~30 critical applications with rollback/parallel-run strategy.”

Yuan-Hsuan Wen

Screened

Intern Software Engineer specializing in AI agents, RAG pipelines, and semiconductor systems

Taipei, Taiwan3y exp

“Built a web-based interface that connects an internal bug system to an LLM for initial debugging and issue classification, aiming to boost QA and software engineer efficiency while balancing latency and accuracy. Worked as a one-person project and managed constraints like limited hardware and difficulty extracting team debugging context, relying on manager communication and rapid modeling to validate direction.”

Rom Manzano

Screened

Executive technical founder and full-stack engineer specializing in AI, SaaS, and FinTech

New York, NY15y exp

“Engineer coming out of a venture studio as it winds down, now seeking another zero-to-one environment with strong studio support and go-to-market playbooks. They show a thoughtful founder mindset centered on rapid shipping, design-partner validation, lean execution, and testing whether users will actually pay for a workflow-specific solution.”

“Engineering leader with experience at Vertex and Salesforce, combining org leadership with hands-on architecture work. He led a 40-person team through execution and quality improvements, drove legacy modernization and SaaS transition, and launched a 0-to-1 voice capability in CRM while also applying AI to code migration and developer productivity.”

UDAY JARAJAPU

Screened

Executive engineering leader specializing in AI-native products and large-scale platforms

Fremont, CA22y exp

“Experienced cross-functional operator with background in AI, edtech, consumer mobile, cloud, and real estate search, including roles at Apple, AWS, and Trulia. Currently building Typerighter, an AI-native writing workspace focused on compliance, authenticity, and human-verifiable content, with a nuanced understanding of institutional requirements and startup/accelerator dynamics.”

“Built and shipped an AI-powered resume analysis and job-matching product end to end across React, TypeScript, FastAPI, OpenAI, LangChain, and FAISS. Strong in practical LLM systems design, including RAG, structured outputs, evals, monitoring, and human-in-the-loop decision support, with a reported 35% improvement in recruiter-validated matching accuracy.”

Jim Glassman

Screened

Executive Technology Leader specializing in Enterprise AI, Cloud Architecture, and Data Platforms

Houston, TX16y exp

“Senior data/technology executive who stays hands-on: currently building a Go micro-kernel orchestration layer for medical AI agents to boost concurrency and enforce HIPAA/PHI controls, achieving 26x throughput on migrated workloads. Has led large-scale transformations across healthcare and financial services, including a 45-day data warehouse rebuild at Elara Caring and a data/ML roadmap at Acelity credited with $230M in annual revenue impact prior to 3M acquisition.”