Pre-screened and vetted.
Junior Software Engineer specializing in cloud-native microservices
Mid-level Full-Stack Developer specializing in cloud-native web applications
Mid-Level Software Engineer specializing in Java/Spring microservices for FinTech
Mid-Level Software Engineer specializing in cloud-native microservices and Healthcare IT
Mid-Level Full-Stack Software Engineer specializing in Java, Spring Boot, and React
Junior Front-End/Full-Stack Software Engineer specializing in accessible web applications
Mid-level Full-Stack Software Engineer specializing in cloud-native systems and GenAI
Senior AI/ML Engineer specializing in computer vision, GenAI, and 3D spatial analytics
Senior Full-Stack Developer specializing in Java microservices and cloud platforms
Senior Java Full-Stack Developer specializing in cloud-native microservices and FinTech
Mid-level Full-Stack Engineer specializing in FinTech and cloud-native platforms
Mid-Level Software Engineer specializing in Java/Spring Boot microservices and cloud DevOps
Mid-level Full-Stack Developer specializing in FinTech microservices
“Backend engineer currently at Citigroup working on real-time transaction processing systems with Kafka. Stands out for using AI tools pragmatically in a regulated banking environment to improve debugging, testing, and developer productivity while keeping human control over architecture, security, and performance decisions.”
Senior Full-Stack Java Engineer specializing in cloud-native microservices and GenAI
“Deloitte engineer who built and shipped AI-powered, Kafka-driven workflow automation for transportation/document processing, including LLM-based semantic search. Strong in production reliability (idempotency, offset management, retries), observability (Datadog/CloudWatch), and database performance tuning (PostgreSQL/Flyway), with measurable latency improvements.”
Mid-level Software Engineer specializing in cloud-native distributed systems
“Full-stack engineer with Bank of America experience building and owning a customer portfolio dashboard end-to-end, from requirements through launch and ongoing iteration. They combine React/Spring Boot/PostgreSQL implementation with strong performance tuning, real-time data handling, and UX improvements, and cite adoption by roughly 12,000 active internal users.”
Mid-level Software Engineer specializing in AI platforms and full-stack systems
“Software developer with a one-year Philips co-op who has already applied AI-assisted coding in production, not just side projects. Stands out for using multi-agent development setups with task-specific sub-agents and a clear human-led orchestration philosophy focused on context, quality control, and security.”
Senior Java Full-Stack & DevOps Engineer specializing in cloud-native microservices
“Software engineer with a CS/Computer Engineering background who has worked on ML/NLP (Hugging Face, clinical NLP, text generation and structured extraction) and has a school robotics project integrating a trained ML model with microprocessor-controlled hardware to drive motor movement and writing. Currently focused on building and deploying applications and ML models to AWS/Azure using Docker, Kubernetes, and CI/CD; targeting ~$150K compensation.”
Mid-level Full-Stack Java Developer specializing in cloud-native microservices
“Full-stack engineer focused on enterprise, cloud-native microservices—building Spring Boot backends and React/Angular front ends with strong security (OAuth/JWT), AWS infrastructure (RDS/S3), and containerized deployments (Docker/Kubernetes). Has delivered data-heavy order/account/transaction platforms and healthcare solutions including EHR integrations for secure patient data exchange, with emphasis on testing, performance tuning, and reliability (load testing).”
Mid-level Full-Stack Java Developer specializing in FinTech and Healthcare platforms
“Software engineer who built internal operations/monitoring dashboards for real-time trading and money-movement systems, emphasizing auditability and rapid iteration. Deep experience with microservices on Azure using Kafka/RabbitMQ, plus strong testing discipline (JUnit/Mockito/Testcontainers, contract/E2E) and observability patterns (correlation IDs, centralized logging, distributed tracing) to reduce incident triage time and improve resilience.”