Pre-screened and vetted.
Senior Backend Engineer specializing in FinTech and distributed systems
“Backend-focused engineer with deep Java/Spring expertise in fintech and SaaS integrations, including high-scale financial data pipelines and partner-facing APIs. Most notably re-platformed a 100M+ record ETL system to a custom concurrent Spring Batch architecture that cut failures dramatically and reduced infrastructure costs by over 90%, while also leading enterprise-grade event-driven integrations for customers like Bosch and Amazon.”
Mid-Level Software Engineer specializing in distributed microservices and real-time systems
“Software engineer with production experience at DraftKings and SRC, owning high-impact platform changes like early-start lineup validation fixes and a multi-service refactor to support dual-role players (e.g., Ohtani) using backward-compatible, feature-flagged rollouts. Has embedded onsite with military users to rapidly ship improvements to a COP/TAK mapping integration (TrackSync), and leverages AI tools (Claude) to accelerate learning and delivery in new domains (e.g., ESP32 smart deadbolt project).”
Mid-Level Software Engineer specializing in microservices and cloud data pipelines
“Full-stack engineer with end-to-end ownership across React/TypeScript frontends, Spring Boot/Node microservices, and production ops on Docker/Kubernetes and AWS (ECS/CloudWatch). Built real-time healthcare eligibility and analytics systems at Cigna and an early-stage seller onboarding platform at Flipkart, driving measurable performance gains (35–40% latency/throughput improvements) through event-driven Kafka pipelines, Redis caching, and strong reliability/observability practices.”
Mid-level Full-Stack Java Developer specializing in cloud-native microservices
“Software engineer with strong compliance-domain experience who built a customer-facing compliance and reporting dashboard using React/TypeScript with Spring Boot microservices. Demonstrates mature production engineering practices—contract-first APIs, event-driven architecture (Kafka/RabbitMQ), caching (Redis), and robust CI/CD + observability (Prometheus/Grafana/ELK)—and also created a Python-based audit automation tool adopted into the standard release process.”
Engineering Leader and Former CTO specializing in scalable cloud platforms
“Entrepreneurial builder using Claude Code to rapidly prototype multiple product ideas and validate them with target users via social channels. Created and launched NotePulse (a lower-priced Notionlytics alternative), acquiring a dozen early users through Reddit-driven discovery and light paid experiments, with a strong emphasis on MVP scoping and product polish.”
Senior Software Engineer specializing in identity, cloud-native microservices, and reactive web apps
“Product-focused full-stack engineer with Walmart and Dell experience who built and shipped a real-time engagement dashboard end-to-end (Kafka Streams, Spring Boot, React/TypeScript/D3) used daily by business teams, moving them from next-day reports to real-time decisioning. Strong in performance/reliability (Redis caching cut latency ~40%, 90%+ test coverage, Prometheus/CloudWatch monitoring) and production operations on AWS/EKS including handling a cascading failure from a memory leak with zero-downtime rollback and redeploy.”
Engineering Director specializing in distributed systems and enterprise cloud platforms
“Engineering lead/player-coach working on project management software, owning a high-impact scheduling algorithm rewrite focused on performance, maintainability, and documentation after prior team turnover caused regressions. Previously at EOX Vantage, helped an insurance client modernize monolithic workflows by scoping ambiguous requirements into a roadmap and shipping a day-one MVP before iterating with value-add features.”
Mid-level Backend Software Engineer specializing in AWS cloud and FinTech platforms
“JP Morgan engineer and Texas A&M student web developer who has owned production systems end-to-end, including a real-time ML training workflow that improved internal search relevance by 30%. Experienced with AWS cloud migrations and operating containerized services on ECS with CloudWatch+ELK observability, Terraform infra, and Spinnaker CI/CD; also built event-driven pipelines with RabbitMQ and Elasticsearch at 1M+ record scale.”
Mid-level Data Engineer specializing in cloud data pipelines and enterprise data platforms
“Data engineer/backend engineer who owns large-scale, real-time event pipelines on AWS end-to-end, including a petabyte-scale CDC ingestion flow from multiple Postgres DBs into Redshift. Re-architected a legacy DynamoDB+S3 approach into a Delta Lake + DuckDB/PyArrow-compatible design, improving performance dramatically (e.g., ~600s to ~10s for 1k records) and increasing reliability at high file volumes.”
Mid-level AI Engineer specializing in GenAI, NLP, and MLOps
“LLM/agentic-systems engineer with PayPal experience hardening an LLM-powered fraud support assistant from prototype to production, focusing on low-latency distributed architecture, rigorous evaluation/testing, and security/compliance. Comfortable in customer-facing and GTM contexts—runs technical demos/workshops, builds tailored pilots, and aligns sales/CS with engineering to close deals and drive adoption.”
Mid-Level Software Engineer specializing in Java microservices and cloud-native systems
“Full-stack engineer (SAP Labs experience) who built an end-to-end, real-time fraud detection system on Java 11/Spring Boot microservices with Kafka event streaming and a React/Redux analytics dashboard with WebSocket updates. Demonstrated strong production ownership by diagnosing a critical memory leak with Prometheus/CloudWatch + heap dumps and improving performance with Redis caching (40% faster queries), while also modernizing deployments via Kubernetes, Jenkins CI/CD, and Terraform.”
Engineering Leader specializing in Digital Health, AI, and Cloud Platforms
“Senior Engineering Manager at Roche leading two Scrum teams building internally shared (“inner-sourced”) tools and libraries for a healthcare enterprise. Has led security/compliance-first architecture decisions (e.g., Python AI modules running inside a Java container) and front-end modularization (Angular monorepo to module federation), with a strong focus on developer experience via automated Swagger/OpenAPI documentation and robust testing/versioning practices.”
Junior Full-Stack Software Engineer specializing in cloud-native microservices
“Backend engineer with hands-on IoT and AI product work: built a decoupled Raspberry Pi + AWS IoT Core weather monitoring backend and a Dockerized FastAPI LLM service on AWS ECS using OpenAI/HuggingFace with an emerging RAG layer. Also delivered measurable performance gains at DAZN by redesigning event-driven/serverless ingestion (SNS, S3->Lambda->DynamoDB), cutting latency ~30% and boosting throughput ~25% while automating ~90% of manual sync work.”
Senior Python Full-Stack Developer specializing in cloud-native microservices and data platforms
“Backend/data engineer from Oliver Wyman who built and ran production Python (FastAPI) services on AWS (ECS/Lambda/API Gateway) supporting risk modeling and regulatory reporting. Strong in reliability/observability, Glue-based ETL with data quality controls, and legacy SAS-to-Python modernization with rigorous parity validation; also demonstrated measurable SQL performance wins and cost-control improvements in serverless scaling. Based in Raleigh, NC and can travel onsite for important Bethesda-area meetings.”
Junior Full-Stack AI Engineer specializing in LLM apps and RAG systems
“Built and shipped a production LLM-powered “Vet agent” that automates pet symptom intake across multimodal inputs (images/files/text/speech) and provides analysis/home-care guidance, reaching thousands of daily active users within two months. Demonstrates strong agent engineering fundamentals: state-machine orchestration with structured JSON, tool/schema validation, high-availability routing/failover, and rigorous offline/online evaluation loops with trace-driven reliability improvements.”
Principal Cloud & Infrastructure Engineer specializing in reliability and regulated data platforms
“Founder/CTO-type startup leader who has built cloud-native data and AI platforms from scratch while owning both technical vision and product direction. Brings rare end-to-end startup experience spanning zero-to-one building, growth-stage execution, and fundraising from early stage through exit, with a strong ability to translate technical complexity into clear investor narratives.”
Executive AI and enterprise software leader specializing in industrial SaaS
“30-year Silicon Valley startup veteran who built Pratexo, an intelligent edge analytics company focused on the energy transition, raised $15M in seed funding, and landed a major partnership with ABB. He has spent the last decade continuously advising startups and brings deep familiarity with VC and accelerator ecosystems including YC and ABB's SynerLeap.”
Junior Machine Learning Engineer specializing in AI, computer vision, and data systems
“Built and owned an end-to-end AV operations automation and dashboarding platform for USC event operations, used daily to coordinate hundreds of live events. Delivered a React/TypeScript full-stack system integrating Smartsheet APIs with strong reliability practices (typed contracts, validation/fallbacks, safe rollouts) and experience with queue-based microservice patterns (idempotency, retries, DLQs, monitoring).”
Mid-level Full-Stack Engineer specializing in cloud microservices and FinTech
“Software engineer with experience across enterprise (AIG, MSCI) and an early-stage startup (Job Map), owning production systems end-to-end. Built secure insurance microservices on Spring Boot with JWT/RBAC and AWS-based CI/CD/observability, plus Kafka streaming pipelines for financial data. Also shipped a GenAI personalization MVP using FastAPI and LLM APIs in a high-ambiguity startup environment.”
Entry-level Full-Stack Developer specializing in logistics and AI-powered web applications
“Backend engineer who led the end-to-end modernization of FleetView into a scalable, event-driven system supporting 1,000+ users and 13,000+ assets, cutting API latency by ~40%. Also built an AI-powered exit interview analytics pipeline on Azure using GPT-4o with strong guardrails, validation, and evaluation practices, showing a rare mix of production backend rigor and applied LLM workflow experience.”
Mid-level Software Engineer specializing in distributed systems and AI-powered platforms
“Software engineer with experience spanning an SEL internship and Walmart, combining backend/data pipeline work (Python, Kafka, relational DBs) with DevOps practices (Docker, Grafana, GitHub/Jenkins CI/CD, GitOps). Notably contributed to a REST-to-GraphQL migration aimed at reducing cloud utilization and implemented testing strategies to validate the transition.”
Mid-level Software Developer specializing in backend microservices for healthcare and FinTech
“Built and deployed an AI-powered insurance claims fraud platform end-to-end using Java/Spring Boot, Kafka, OpenAI, pgvector, and AWS EKS. Stands out for combining LLM/RAG architecture with production-grade scalability and observability, delivering measurable impact including 62% less manual review, 40% better fraud precision, 37% higher throughput, and 99.95% uptime.”
Mid-level Software Engineer specializing in backend systems for FinTech
“Senior software engineer with hands-on experience leading multi-agent AI workflows in financial trading infrastructure. Most notably, they applied a specialized agent setup on a high-frequency trading backend to cut delivery time from three weeks to ten days while improving validation against risk, performance, and compliance requirements.”
Mid-level Software Developer specializing in backend microservices and cloud platforms
“Full-stack product engineer with strong React and TypeScript depth who has owned dashboard features end-to-end, from UI architecture and rendering optimization through Spring Boot APIs and database query tuning. Particularly compelling for startup or high-growth teams: they’ve shipped 0→1 internal operations platforms, prioritized MVP workflows effectively, and iterated post-launch using user feedback, logs, and usage metrics.”