Pre-screened and vetted.
Mid-Level Java Developer specializing in FinTech microservices
“Backend/platform engineer with deep payments experience who built and operated a real-time transaction routing service end-to-end on AWS (Spring Boot, PostgreSQL/RDS, Redis, Kubernetes), delivering ~40% latency reduction and 99.99% uptime via strong resiliency and observability practices. Also productionized an internal LLM-powered RAG knowledge assistant with guardrails and a user-feedback-driven evaluation loop, and has led incremental monolith-to-microservices modernization using Strangler Fig and shadow traffic.”
Mid-Level Software Engineer specializing in real-time data pipelines and ML deployment
“Ticketmaster data engineer who built CDC-driven Kafka pipelines feeding Snowflake for analytics and data science teams. Hands-on in production operations—scaled Kafka during sudden playoff-driven transaction spikes and improved monitoring for preemptive scaling. Known for using small-batch experiments and quantitative metrics to align stakeholders and drive cost-saving architecture changes (e.g., buffering to reduce AWS Lambda invocation frequency).”
Intern Full-Stack Engineer specializing in AI and distributed systems
“Full-stack product engineer who has designed and shipped production web experiences in EV charging, trading, automotive companion apps, and AI systems. Stands out for owning user-facing React experiences through backend integration and production monitoring, with a strong bias toward reliability in real-time and high-stakes workflows. Also has early-stage Scale AI experience building a Text-to-SQL agent stack with Python, PostgreSQL, Redis, Kafka, and AWS.”
Senior Backend & Infrastructure Engineer specializing in cloud-native distributed systems
“LLM infrastructure engineer who built a production-critical real-time personalization and memory retrieval system for a user-facing product, adding <100ms P99 latency while improving relevance ~20–25% and holding SLA through 3x traffic. Experienced designing tiered retrieval backends (Redis + vector store), deploying on Kubernetes with autoscaling/circuit breakers, and running rigorous observability, incident response, and agent evaluation (shadow traffic, A/B tests, regression/replay).”
Mid-level Software Engineer specializing in consumer platforms and FinTech
“Full-stack product engineer with deep JavaScript/TypeScript expertise who has led backend architecture for FanDuel's sportsbook platform and shipped high-scale systems serving roughly 400 million requests per day. Combines React/React Native product delivery with strong performance and resiliency engineering, including major latency gains, CDN/cache improvements, and features used by millions at both FanDuel and Max.”
Intern/Junior Software Engineer specializing in backend systems and applied AI
Senior Full-Stack Software Engineer specializing in cloud-native platforms and Healthcare IT
Mid-level Software Engineer specializing in AI-driven systems and scalable backend services
Intern Software Engineer specializing in cloud APIs and full-stack development
Senior QA Test Engineer specializing in automation and AR/VR testing
Engineering Manager specializing in cloud-native platforms across AdTech and FinTech
Entry Software Engineer specializing in distributed systems and AI applications
Mid-level Backend Software Engineer specializing in distributed systems and payments
Mid-Level Software Engineer specializing in backend microservices and cloud-native ML platforms
Senior Software Engineer specializing in FinTech compliance systems
Senior Site Reliability Engineer specializing in multi-cloud, Kubernetes, and observability
Mid-level Software Engineer specializing in AWS, full-stack development, and AI data systems
“Backend engineer who built a Python-based data profiling/statistics platform processing up to 50M rows and ~300 metrics, using a DAG execution model, multithreading, and smart caching to cut processing time by up to 70%. Also improved PostgreSQL query performance from 12s to 2s via indexing/query rewrites, integrated an LLM (LangChain + OpenAI) for explainable “chat with the pipeline” functionality, and designed an AWS EC2+SQS architecture for scalable, isolated per-user processing.”
Mid-level Technical Consultant specializing in Appian delivery and data/AI workflow automation
“Appian consultant/engineer focused on insurance and financial services modernization and AI-enabled workflows. Built and productionized an AI-driven insurance submission intake system (email ingestion, classification/extraction, HITL review) cutting processing time from 2+ hours to under 10 minutes, and delivered semantic smart search with guardrails and UAT-driven ranking improvements. Also partnered with a global bank CTO org, running sessions with 200+ senior leaders to automate regulatory/board metric reporting via platform integrations and attestation.”
Mid-level Full-Stack Engineer specializing in AI-driven data platforms
“Full-stack engineer with 5+ years of experience who built real-time data visualization and analytics systems at Uber, spanning React/TypeScript frontends, Node/GraphQL services, Kafka pipelines, and PostgreSQL. Particularly compelling for teams needing a hands-on builder who can turn ambiguous customer needs into scalable products, and who has also applied RAG with LangChain/OpenAI over 1.8M support files to surface actionable insights.”
Senior Full-Stack Engineer specializing in scalable web platforms
“Software engineer with 5+ years of experience building and scaling high-traffic web systems, including e-commerce-style purchasing/reservation flows and broker back-office platforms. He has hands-on experience across Next.js front ends, Python integrations, Go load-testing tools, and MySQL/Redis-backed architectures, with notable exposure to financial reporting, MT5 integrations, and commission logic.”
Senior Software Engineer specializing in cloud-native backend and distributed systems
“Backend engineer focused on Python/FastAPI microservices running on Kubernetes (AWS EKS) with strong GitOps/CI/CD ownership (GitHub Actions + ArgoCD). Demonstrated measurable performance wins (p95 latency cut from >1s to <200ms) and production reliability work across Kafka/Redis streaming and cloud-to-on-prem migrations (RDS/S3 to Postgres/MinIO) using parallel validation and checksum-based consistency checks.”