Pre-screened and vetted in Texas.
Staff Software Engineer specializing in large-scale commerce and payments
Staff Software Engineer specializing in cloud-native healthcare and payments platforms
Senior Backend Engineer specializing in Python and AWS serverless systems
“Backend/data engineer with Amazon supply-chain experience building production serverless Python services and ETL pipelines on AWS (Lambda, API Gateway, S3, RDS, Glue). Has modernized legacy SAS jobs into Python with rigorous parity testing and phased migrations, and has delivered major SQL performance gains (minutes down to seconds) through indexing and partitioning.”
Staff Full-Stack Engineer specializing in cloud microservices and AI-enabled platforms
Mid-Level Software Development Engineer specializing in AWS serverless and backend APIs
Mid-level Full-Stack Developer specializing in AWS modernization and Java/Angular
Mid-level Software Engineer specializing in cloud and full-stack web development
Mid-level Backend Software Engineer specializing in AWS microservices and distributed systems
Director-level Software Engineering Leader specializing in AI, data, security, and cloud
Mid-level Full-Stack Developer specializing in MERN and AWS microservices
“Backend engineer with experience at MetLife and Amazon focused on security and control for internal and customer-facing services. Emphasizes contract-first Python/FastAPI APIs with strong auth (JWT + RBAC/claims), data-layer isolation (RLS/tenant scoping), and reliability practices like incremental refactors, rollback planning, and idempotency to handle retry-driven failure modes.”
Mid-Level Full-Stack Software Engineer specializing in AWS cloud and microservices
“Backend/LLM engineer who built a production-critical Amazon Bedrock + RAG correction and compliance layer for employee communications, integrating tightly with existing Spring Boot/AWS microservices to reduce manual review while keeping outputs explainable and auditable. Also designed an event-driven system processing 10M+ events/day (SQS/Lambda/DynamoDB/Elasticsearch) and handled on-call incidents with strong observability and reliability patterns (idempotency, retries, hotspot mitigation).”
Mid-level Software Development Engineer specializing in FinTech distributed systems
Mid-Level Full-Stack Software Engineer specializing in cloud-native data platforms
“LLM/agentic systems practitioner who specializes in moving customer prototypes into production within microservices environments, emphasizing reliability, latency, security, and measurable success metrics. Experienced in real-time troubleshooting using logs/traces and in enabling adoption through hands-on developer workshops (including live coding in Java Spring Boot) and pre-sales POCs that address technical objections and integration risk.”
Mid-level Software Engineer specializing in backend systems and automation
Senior Frontend/Product Engineer specializing in React, TypeScript, and dashboard UX
Mid-Level Software Engineer specializing in payments, risk analytics, and cloud-native microservices
Mid-level Software Development Engineer specializing in C++ and EDA toolchains
“Worked at AMD on Vivado tool releases, focusing on adding and integrating new IP/SoC functionality into the Vivado flow and validating expected behavior through testing. Comfortable engaging with customers and open to travel for hands-on customer-facing work.”
Mid-level Full-Stack Java Developer specializing in cloud-native microservices and FinTech
“Full-stack Java engineer (4+ years) who led end-to-end modernization of high-latency order management systems into cloud-native reactive microservices (Spring WebFlux) and built real-time React/Redux dashboards, reporting 99.98% uptime and 22% infra cost savings. Also headed a production RAG-based Order Support Bot at Dell Technologies with embeddings + MongoDB semantic search, automated validation and human fallback, plus CI/CD-driven LLM eval loops to reduce hallucinations.”
Mid-level Full-Stack Engineer specializing in enterprise AI systems
“Built and productionized an AI NL-to-SQL capability inside legacy accounts receivable software (React + Spring Boot + Postgres/pgvector RAG), adding semantic caching and a SELECT-only validation layer to satisfy infosec. Achieved measurable impact (3 days to seconds turnaround, 60% token cost reduction, 50% latency reduction) with strong adoption (40 analysts, 50+ queries/week) and documented/monitored via Confluence + logging and user feedback loops.”