Vetted Full-Stack Development Professionals

Tara Munjuluri

Screened

Junior Software Engineer specializing in full-stack and AI systems

Ames, IA3y exp

“Backend-focused engineer with end-to-end ownership experience on internal platforms at John Deere, including a workforce and skills system that cut manual review time by 40%. Brings a strong reliability and compliance mindset across Java/Python microservices, AWS infrastructure, and production operations, and has also built an LLM-powered RAG system over 1M+ records with emphasis on grounded outputs and observability.”

“Data/analytics engineer who built and operated a DocuSign-based real-time analytics platform end-to-end, processing 20–50k webhook events/day with ~99.5% reliability. Strong in idempotent event processing, schema-evolution-safe ingestion (raw JSON + dynamic parsing), and serving data via versioned, low-latency REST APIs with solid CI/CD and observability.”

“ML/AI engineer with hands-on ownership of production document intelligence and GenAI systems, spanning model experimentation, AWS deployment, monitoring, and iterative optimization. Stands out for turning document-heavy workflows into reliable, near real-time products with measurable gains in accuracy, latency, and manual-effort reduction, while also shipping citation-grounded RAG features that drove user trust and adoption.”

Kaustav Mukherjee

Screened

Staff Product Leader specializing in AI, CRM, Martech, and Commerce platforms

12y exp

“Product leader with experience spanning Intuit, Taylor Brands Innovation Lab, and Head of Product at Content Analytics, combining strong product architecture judgment with practical AI/ML execution. They led a QuickBooks proposals rebuild that improved SMB job win rates and an AI sizing initiative that doubled digital adoption while reducing fit-related exchanges, and they also built an AI-powered career coaching app grounded in a human-centered AI philosophy.”

Harsh Sanas

Screened

Intern Full-Stack Engineer specializing in AI and distributed systems

Los Angeles, CA2y exp

“Full-stack product engineer who has designed and shipped production web experiences in EV charging, trading, automotive companion apps, and AI systems. Stands out for owning user-facing React experiences through backend integration and production monitoring, with a strong bias toward reliability in real-time and high-stakes workflows. Also has early-stage Scale AI experience building a Text-to-SQL agent stack with Python, PostgreSQL, Redis, Kafka, and AWS.”

“AI engineer at Anote.ai who built and shipped a production multi-agent LangGraph/LangChain/Ray RAG platform for enterprise search and workflow automation, supporting 3 commercial products and 100+ developers. Drove measurable gains (30% accuracy improvement, lower latency) and improved reliability with Redis-based state checkpointing, message-queue synchronization, and Milvus retrieval optimizations, while partnering with PMs/clients to add transparency features like confidence scores and real-time logs.”

“Built and architected ML-integrated payment processing systems for PlayStation at Sony Interactive Entertainment, covering fraud determination, provider routing optimization, and model-training feedback loops in production. Brings a strong reliability and observability mindset, with concrete experience designing fallbacks, retries, correlation-ID tracing, and statistically grounded evaluation for non-deterministic systems.”

“Software engineer at Paradigm who is deeply hands-on with agentic development workflows and AI-assisted coding. He built an in-house OAuth layer to replace a third-party service and reduce projected integration costs, and also created an "ambient agent" that proactively responds to user behavior on the website. He stands out for combining full-stack architecture thinking with a disciplined, model-aware workflow for designing, implementing, and reviewing AI-generated code.”

“Senior engineering leader from IBM who has built and scaled enterprise AI/GenAI platforms across hybrid and multi-cloud environments, combining executive-level org leadership with hands-on debugging of production distributed systems. Particularly compelling for Director/VP roles needing someone who can unify architecture, platform strategy, and engineering execution across multiple teams.”

Rediet Gesesse

Screened

Mid-level Software Engineer specializing in FinTech and full-stack platforms

San Francisco, CA4y exp

“Built a kitchen capacity management system for merchants, owning deployment through stabilization and continuously tuning capacity based on fulfillment and cancellation outcomes. Also designed customer-support decision workflows for refunds/credits with a focus on fraud cost reduction, and has hands-on experience with Kafka, Flink, relational databases, and production incident mitigation via feature-flag rollbacks.”

Polat Akbiyik

Screened

Mid-level Software Engineer specializing in FinTech and trading systems

Remote4y exp

“Full-stack builder with strong product and AI systems ownership, spanning data infrastructure, React/TypeScript apps, and LLM-powered agents. Particularly notable for building a crypto analytics MVP with catalog-driven ETL, config-based charting, and AI-generated dashboards, plus an options-strategy agent and an ops automation tool that cut a 10-minute workflow down to 10 seconds.”

“Frontend-leaning product engineer who has owned complex, data-heavy interfaces across Stitch Fix, Amplitude, Salesforce, and C3Drone. Stands out for modernizing legacy UIs into React, improving performance for large and real-time datasets, and stepping beyond frontend into backend sync logic, middleware, and query/parser work to ship collaborative product features.”

“Data engineer/backend developer with experience owning end-to-end, high-volume data pipelines for ML/analytics using Python, Airflow, SQL, and PySpark, reporting ~30% error reduction through improved reliability and data quality checks. Has also built Django-based REST APIs with caching/pagination and strong versioning practices, and operated external data collection/web scraping pipelines with anti-bot measures, monitoring, retries, and idempotent backfills.”

Rucha Joshi

Screened

Junior Software Engineer specializing in full-stack and backend development

Austin, TX2y exp

“Builder of multiple zero-to-one consumer applications, including an anonymous writing feedback tool with a Gemini-powered chatbot, a dietary-profile recipe product using LLM-based substitutions, and a live-updates Sports Hub. Stands out for hands-on full-stack execution, iterative AI experimentation, and a quantified 80% reduction in time users spent finding recipe-compatible ingredients and options.”

Jiajun Huo

Screened

Mid-level Software Engineer specializing in AI, data infrastructure, and LLM systems

Urbana, IL4y exp

“Built end-to-end data and automation systems at Sonic SVM, spanning Python/FastAPI/Kafka/Spark ingestion pipelines, warehouse analytics, and Playwright automation for brittle SSO-protected dashboards. Stands out for combining backend/data engineering with strong observability and reliability practices, plus a pragmatic ability to turn messy manual business processes into measurable self-serve workflows.”

Christopher Kirby

Screened

Executive engineering leader specializing in platform engineering, AI systems, and SaaS

Detroit, MI24y exp

“Senior engineering executive who has repeatedly rebuilt and scaled product engineering organizations in high-growth environments, including restarting Rocket Auto’s stack from scratch and hiring 100+ engineers during StockX’s hypergrowth phase. Particularly differentiated by being unusually hands-on for an executive leader, with active open source work and a strong focus on AI-native engineering workflows, developer automation, and modern architecture transformation.”

“Product leader with a rare cross-industry track record spanning fire departments, supply chain analytics, renewable energy, and staffing. They have led complex zero-to-one and migration-heavy product launches, including shipping 3 new public-safety products during COVID, driving 7x faster customer migrations and major revenue uplift, while also commercializing ML-powered analytics products that increased ARR.”