Pre-screened and vetted.
Mid-Level Full-Stack Java Developer specializing in Spring Boot and Angular/React
Senior Data/GenAI Engineer specializing in cloud-native ML, RAG, and real-time data platforms
Senior Full-Stack Software Engineer specializing in scalable microservices and cloud platforms
Mid-level Full-Stack Developer specializing in AWS modernization and Java/Angular
Mid-level Software Engineer specializing in cloud infrastructure and distributed systems
Director-level Mobile App Engineer specializing in Flutter, AI, and web development
Mid-level Software Engineer specializing in backend systems and FinTech
Mid-level Software Engineer specializing in cloud platforms and AI-integrated full-stack development
“Backend engineer who built Flask-based internal APIs supporting GenAI-driven provisioning/diagnostics (Outpost/AWS Outposts-like environment), with deep hands-on optimization across Postgres/SQLAlchemy (2s to <200ms endpoint improvement). Experienced integrating ML/LLM workflows via AWS SageMaker and Bedrock, and designing multi-tenant isolation plus high-throughput Redis-backed background task pipelines (minutes to seconds).”
Mid-level AI/ML Engineer specializing in FinTech and fraud detection
“ML/backend engineer with PayPal experience building high-stakes production systems, including a GenAI internal support assistant and a real-time fraud scoring pipeline. Strong in Python/FastAPI, model-serving infrastructure, RAG architecture, and production observability, with clear readiness to transition those backend patterns into a TypeScript stack.”
Mid-level Full-Stack Python Developer specializing in cloud-native banking applications
“Backend engineer who built a low-latency real-time transaction API in Python/Flask, with strong depth in PostgreSQL/SQLAlchemy performance tuning (time-based partitioning, indexing, connection pooling). Has production experience integrating ML scoring and OpenAI-style APIs with safety/latency controls, and designing multi-tenant isolation strategies including per-tenant pooling/caching and premium-tenant isolation.”
Mid-level Full-Stack Software Engineer specializing in web platforms
“Full-stack web developer with hands-on ownership of products from requirements through launch and maintenance, building across React and Node.js. Stands out for balancing product usability with technical performance, including API/database optimizations that improved performance by about 30% and shipping real-time dashboard features with scalable frontend/backend tradeoffs.”
Mid-level Software Engineer specializing in distributed data infrastructure
“Engineer who uses AI in a disciplined, practical way—leveraging it to speed debugging, generate edge-case tests, and improve coverage while retaining ownership of system design and production validation. Has experimented with chained AI tools but prefers simpler workflows when they reduce noise and review overhead.”
Junior Full-Stack Developer specializing in Java microservices and cloud platforms
“Full-stack engineer (~2.6 years) with strong Java/Spring Boot backend experience and React/Angular frontend exposure, who has worked on enterprise-scale systems at Dell processing ~1.8M daily transactions/events. Built secure, partner/internal-facing APIs (OAuth2/JWT) across 14 integrations and implemented Kafka-based order/payment workflows with idempotency and sub-700ms processing targets, plus CI/CD and Selenium-based release validation.”
Junior Software Engineer specializing in identity and backend systems
“Sole engineer on a large-scale authentication migration moving 350+ tenants from password-based auth to OAuth 2.0 client credentials, delivering zero downtime, full adoption, and no support tickets. Also has early hands-on experience with agentic LLM proof-of-concepts and has built structured workflow tooling to reduce ambiguity in customer-to-engineering handoffs.”
Senior Software Engineer specializing in Python backend systems on AWS
“Backend/data engineer from ASML who modernized a legacy SAS-based statistical processing system into a cloud-native AWS platform (Lambda/FastAPI, Step Functions/EventBridge, Glue, S3/RDS) with strong reliability and data-quality practices. Demonstrated measurable performance wins (RDS query reduced from 90+ seconds to <5 seconds) and hands-on incident ownership for production ETL pipelines.”
Mid-level Full-Stack Developer specializing in Java, microservices, and cloud platforms
“Backend-focused engineer who uses AI pragmatically as a force multiplier rather than a substitute for engineering judgment. They stand out for applying structured, agent-style workflows to code generation, debugging, and production log analysis while maintaining strong emphasis on correctness, performance, and reliability in backend and microservices environments.”
Mid-level Backend Software Engineer specializing in Java/Spring microservices and FinTech
“Backend engineer with Apple experience who owned production platform improvements end-to-end, including a Redis caching layer that cut API latency ~35–40% and reduced DB load. Has hands-on on-call/incident response and observability (CloudWatch), plus experience scaling Docker/Kubernetes microservices and operating Kafka-based telemetry pipelines with schema evolution, deduplication, and replay/backfill handling.”
Senior Cloud Platform Engineer specializing in AI infrastructure and distributed systems
“Engineer with hands-on experience shipping production Python integrations and designing for reliability from day one, including idempotency, retries, dead-letter handling, contract checks, and full observability. Also brings web automation experience with Puppeteer and has implemented high-availability failover using load balancer liveness checks, backup environments, and cold standby architecture.”
Junior Software Engineer specializing in full-stack and backend development
“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.”