Pre-screened and vetted.
Junior Software Engineer specializing in AI infrastructure and applied machine learning
Senior Full-Stack Engineer specializing in telehealth and commerce platforms
Mid-Level Full-Stack Software Developer specializing in AWS cloud and automation
Junior Software Engineer specializing in distributed systems and streaming platforms
Senior Software Engineer specializing in full-stack platforms and FinTech systems
Junior Frontend Software Engineer specializing in React, TypeScript, and performance optimization
Principal Data Scientist / AI Engineer specializing in healthcare-native AI platforms
Senior Frontend Software Engineer specializing in React, TypeScript, and UI infrastructure
Senior Full-Stack Engineer specializing in AI, cloud, and enterprise platforms
Mid Software Engineer specializing in backend systems and AI-enabled platforms
“Full-stack engineer with hands-on ownership of a support ticket intelligence platform, spanning React/TypeScript frontend work and backend API, PostgreSQL, Redis, and Docker-based deployment. They stand out for driving practical architecture and performance improvements in production, including moving heavy processing async and cutting response times from about 300ms to 150ms while improving reliability.”
Mid-level Software Engineer specializing in backend, cloud, and ML systems
“Software engineer with experience across Goldman Sachs, BYU Broadcasting, Juniper Networks, and an edtech startup (Doubtnut), spanning data migrations, AWS-based media backends, and microservices observability. Built a Redis/ElastiCache caching layer in front of DynamoDB/S3 to improve media delivery latency and cost, and created an SEO indexing automation tool using the Google Search Console API that saved ~15–30 person-hours per day.”
Mid-Level Backend Software Engineer specializing in FinTech platforms
“Backend/platform-focused engineer who builds scalable onboarding and data ingestion pipelines for complex client data formats, emphasizing staged validation, idempotent job boundaries, and safe rollouts behind feature flags. Strong in production diagnostics (Kibana/Logstash, SQL, debugger traces) with a concrete example of finding a regression causing incorrect Tax Loss Harvesting alert counts within a day, and experienced enabling both engineers and customer-facing teams through docs, runbooks, and technical walkthroughs.”
Senior Frontend Engineer specializing in scalable, accessible web applications
“Engineer with startup experience at a Series B company, where they worked through high ambiguity and personally led an observers feature for a video conferencing platform. They also bring B2B SaaS experience building feature-flagged, permission-sensitive products for customers ranging from startups to large enterprises, plus migration experience moving an acquired app from .NET into a React/Next.js ecosystem.”
Senior Full-Stack Engineer specializing in AI platforms and scalable web systems
“Built and shipped production agentic/LLM systems that could safely perform real customer and subscription operations, not just answer questions. Demonstrates unusually strong depth in agent orchestration, tool safety, evals, tracing, and backend workflow design across Node.js/TypeScript, Go, Redis, Postgres, Kafka, and GPT-4.”
Senior Full-Stack Engineer specializing in cloud-native microservices and React
“Backend/data engineer with strong AWS production experience spanning high-traffic FastAPI APIs (Postgres/Redis/Kafka) and serverless+container deployments (Lambda/ECS) managed via Terraform and CI/CD. Has built Glue-based data lake ETL (S3 Parquet, Athena/Redshift) with schema drift/data quality controls, modernized legacy batch systems via parallel-run parity validation, and demonstrated measurable SQL performance wins (60–90s down to 3–5s).”
Mid-Level Software Engineer specializing in Python, data pipelines, and FinTech systems
“Software/data engineer with experience at Google and on Bloomberg-related financial data modernization, building Python pipelines that convert legacy financial datasets into modern structures and iterating based on client feedback (e.g., adding historical change tracking for private placement data). Also built an internal Google usage-metrics dashboard pipeline using Protocol Buffers and scaled execution via sharded parallel cron jobs while scheduling off-hours to avoid impacting a testing tool.”