Vetted API Design Professionals

Haytham Nasri

Screened

Software Engineering Manager specializing in cloud-native mobility and enterprise Java

Amsterdam, The Netherlands15y exp

“Backend/architecture-focused player-coach who designed and built two partner-facing data APIs using a contract-first (OpenAPI) governance model in Java (Quarkus/Spring Boot). Strong in technical standards, incident response, and delivery systems—improved reliability under peak load (DB/index fix) and sped up delivery by streamlining PR/review processes while maintaining production stability.”

“Backend engineer with fintech/AI startup experience who built an Azure serverless, event-driven pipeline for large-scale crypto sentiment analysis and semantic search (OCR/NLP to vector search) and integrated LLM + blockchain data for predictive insights. Demonstrated measurable impact (25% lower retrieval latency, 10% fewer data errors, 15% higher engagement) and has led safe microservices migrations with strong security and reliability practices.”

“Backend/data engineer with strong production experience across Python microservices (FastAPI) and AWS serverless/data platforms (Lambda, API Gateway, Glue, Redshift). Demonstrates reliability and incident ownership (rate limits, retries/circuit breakers, monitoring) and has delivered measurable SQL performance gains (12–15s to <800ms, ~60% CPU reduction). Seeking fully remote work and not open to relocation/onsite meetings.”

“AI engineer who shipped a production KYC facial liveness/recognition pipeline (10k+ monthly verifications), including an on-prem, GPU-hosted Qwen3-VL vision-language fallback to detect spoofing/replay attacks. Also helped build a deterministic multi-agent orchestration layer powering a marketplace with Solana on-chain payments, abstracting blockchain complexity behind an API, and has experience translating real-world needs from non-technical stakeholders (construction) into practical document-reading solutions.”

“Backend-focused engineer who owned an AI mentoring workflow platform built in Django with LangGraph multi-agent orchestration, optimizing it to stay under 200ms latency while scaling past 1,200 active users using profiling, caching, load testing, and OpenTelemetry-style tracing. Also has hands-on experience containerizing and deploying Python/ML services to AWS ECS via GitHub Actions/GitOps, and building reliable real-time pipelines with webhooks and Redis queues (idempotency, backpressure, DLQ).”

“Backend engineer who built an Emergency Alert System with Virginia Tech for the City of Alexandria, focusing on real-time ingestion, secure dashboards, and AI-assisted prioritization. Emphasizes high-stakes reliability with guardrails (hybrid rules+LLM, confidence-based fallbacks), scalable async processing, and defense-in-depth security (JWT/RBAC plus database row-level security).”

Likhith Kumar Yaramala

Screened

Junior Backend/Cloud Software Engineer specializing in microservices and DevOps

India2y exp

“Cloud/DevOps-focused engineer with strong Linux production operations experience, deploying microservices to AWS on Docker/Kubernetes. Has built and operated secure CI/CD (GitHub Actions/Jenkins) and Terraform IaC workflows with approvals, remote state, and drift detection, and has hands-on incident recovery experience in containerized environments; limited direct IBM Power/AIX/PowerHA exposure.”

“Engineering leader/player-coach who redesigned A/B testing and observability infrastructure for real-time audio/video features at 90M+ DAU scale, using Kafka-based ingestion and horizontally scalable aggregation for near real-time metrics. Managed 10–15 engineers, drove >20% infrastructure cost reduction without user-experience regressions, and led major peak-traffic incident response with lasting reliability improvements (load testing, capacity planning, alerting, pre-mortems).”

Owen Wolff

Screened

Junior Software Engineer specializing in full-stack web and systems programming

Washington, DC3y exp

“Junior engineer who built a novel, highly-performant database explorer at Electric Capital: a TypeScript/React UI backed by Zig-compiled WebAssembly that loads data locally for fast filtering/sorting and responsive lazy loading, with CI/CD and Cloudflare-based auth. Also led graphics work on a WebGPU browser game engine capstone, creating TypeScript abstractions over WGSL/shader and GPU buffer complexity to accelerate teammates.”

Abhishek Ingle

Screened

Junior Full-Stack & AI Software Engineer specializing in React/Next.js and LLM systems

Bloomington, IN2y exp

“Backend engineer with hands-on experience building low-latency, high-concurrency real-time chat on AWS (Node.js/Socket.IO/MongoDB) and improving reliability under unstable networks, contributing to ~40% user adoption growth. Also built FastAPI-based AI assistant context retrieval (RAG) APIs with embeddings/vector search, and has strong production experience in rate-limit handling, async refactors with safe rollout, and Supabase Auth/RLS optimization.”

Pranav Zagade

Screened

Junior Software Engineer specializing in full-stack and AI systems

Arizona, USA3y exp

“Built and shipped an LLM-powered support agent for Community Dreams Foundation that automated intake and Jira ticket creation using RAG, structured outputs, and strong production guardrails. Demonstrated practical production AI experience with 92% routing accuracy, 98% uptime, and a 31% improvement in first-response accuracy, plus hands-on work in observability, evals, idempotency, and failure handling.”

“ML engineer with hands-on experience building banking AI systems end-to-end, including a customer-targeting model that improved campaign response rates by about 10%. Also shipped a RAG-based banking FAQ/support feature with safety guardrails and production optimizations around retrieval quality, latency, and cost, plus reusable Python services that reduced duplicate work for other engineers.”

“Built a Personal Finance Copilot, a full-stack AI assistant for transaction search, spending analysis, subscription tracking, and grounded financial Q&A, with multi-step tool-calling orchestration and hybrid retrieval/memory architecture. Stands out for using AI coding agents aggressively to accelerate planning and implementation while maintaining strong ownership of system design, testing, security, and reliability.”

“Built a production LLM/RAG document extraction and game/quiz content workflow using LLaMA 2, LangChain/LangGraph, and FAISS, achieving ~94% accuracy and reducing turnaround from hours to minutes. Demonstrates strong applied MLOps/orchestration (CI/CD, MLflow, Databricks/PySpark), robust handling of noisy/variable document layouts (layout chunking + OCR fallbacks), and practical reliability practices (human-in-the-loop routing, drift monitoring, A/B testing).”

“Early-career backend engineer and solo builder of FrameFindr, an AI/OCR-based marathon photo tagging product used at live events. Demonstrated pragmatic scaling under tight infrastructure constraints (2GB VPS) and hands-on ownership of architecture, API design, auth (Google OAuth/JWT), and a MongoDB-to-MySQL migration with data-integrity safeguards.”

“Backend/data engineer with hands-on production experience across Python/Flask microservices and AWS serverless/data platforms (Lambda, DynamoDB, S3, Glue/PySpark). Demonstrated strong reliability and operations mindset (JWT/RBAC, retries/timeouts/circuit breakers, CloudWatch/SNS alerting) and measurable performance wins (SQL report runtime cut from 10 minutes to 30 seconds). Seeking ~$150k base and cannot travel for onsite meetings for the next 5–6 months due to family medical constraints.”

“At Unar Labs, built and operationalized LLM capabilities inside a cloud-native SaaS product, emphasizing production reliability (fallbacks, observability, cost/latency/quality monitoring) and iterative improvement from user feedback. Also acts as a customer-facing technical lead—running developer demos/workshops and supporting sales through discovery, pilots/POCs, and technical walkthroughs to drive production adoption.”

“Software engineer experienced delivering customer-facing, real-time industrial monitoring dashboards (motors/shafts/turbines) by partnering directly with end users to refine charts, alerts, and performance. Strong in API/platform integrations and production troubleshooting—uses feature flags, logging, validation/mapping, containerization, and performance testing to keep systems stable while iterating quickly.”

“AI/LLM engineer who shipped a production RAG-based knowledge assistant at SparkPlug serving 10,000+ daily users, streaming GPT-4 answers with inline citations over WebSockets. Demonstrated measurable impact (support resolution time cut 18→12 minutes; retrieval precision +~20%) and strong production rigor across ingestion, monitoring/alerting, evaluation, and messy ERP-style data integration with validation, RBAC, and idempotent operations.”

Jayasri Guthula

Screened

Mid-level Applied ML Engineer specializing in LLM evaluation and multimodal agent systems

Remote5y exp

“Full-stack engineer working at the intersection of product and infrastructure, building developer-facing interfaces for AI voice agents in XR/immersive environments plus telemetry-heavy analytics dashboards. Experienced in Postgres telemetry data modeling and performance tuning, and in designing durable multi-step LLM pipelines with idempotency, retries, and strong observability; has operated in fast-moving startup-like teams (Biocom, HandshakeAI).”

“Full-stack product engineer who has built AI-assisted CRM and agent workflows in Project SARA and operational systems like payroll for a staffing platform. Stands out for combining React/TypeScript, Django/Postgres, real-time systems, and LLM orchestration with strong product instincts—delivering measurable gains in response time, conversion, and engineering leverage.”

Tarun Gowda

Screened

Mid-level Software Engineer specializing in AI, backend systems, and cloud platforms

Morristown, NJ3y exp

“Full-stack engineer who helped build and launch an internal genAI platform called GAIL, supporting multiple LLMs, confidential document upload for RAG pipelines, and collaborative chat. Worked across FastAPI, React/TypeScript, AWS/DynamoDB, and Azure, with notable ownership of backend RAG logic, MCP integration architecture, and frontend fixes that improved chat usability.”

“Backend/data engineer focused on AWS-based, low-latency event processing for market data and social-signal sentiment systems. Has led a monolith-to-event-driven migration with feature-flagged incremental rollout, and emphasizes production-grade security (OAuth2/JWT, secrets management, Supabase RLS) and data integrity (deduplication/idempotency) under high-volume spike conditions.”

“Software engineer with end-to-end ownership of a Qt/C++/QML desktop app for monitoring/configuring equipment, including hands-on UI performance optimization. Also built a web-based AI agent interface (React/TypeScript + Python Flask) with strong API contract discipline and async state handling, and improved microservices reliability using idempotency, DLQs, and observability. Created an internal CI/CD automation tool adopted across engineering and operations teams, adding safer rollbacks and better error messaging based on feedback.”