Pre-screened and vetted.
Mid-level Cloud & DevSecOps Engineer specializing in AWS, Java microservices, and SOC operations
Mid-level DevOps/SRE specializing in AWS cloud infrastructure and Kubernetes
Intern/Entry Full-Stack Software Engineer specializing in backend APIs and AWS
Mid-level DevOps Engineer specializing in AWS, Kubernetes, and regulated healthcare platforms
Senior Software Engineer specializing in cloud-native security and API platforms
Mid-level Full-Stack Software Engineer specializing in cloud-native FinTech and insurance systems
Senior Full-Stack Software Engineer specializing in cloud-native FinTech and data pipelines
Senior Unity Developer specializing in AI/LLM systems and multiplayer VR
“Backend/data engineer focused on AWS-native Python systems: built a FastAPI microservice on ECS/Fargate serving real-time analytics at millions of daily requests with strong reliability (OAuth2/JWT, retries/timeouts, correlation IDs) and autoscaling. Also delivered Glue/PySpark ETL pipelines to curated S3 Parquet/Athena with schema evolution + data quality controls, owned Airflow pipeline incidents, and has a track record of measurable performance and cost optimizations (e.g., ~80%+ query latency reduction; reduced logging/NAT/Fargate spend).”
Mid-level AI/ML Engineer specializing in LLMs, RAG, and production GenAI systems
“Built and deployed a production LLM-powered RAG knowledge system to unify operational/policy information across PDFs, wikis, and databases, emphasizing auditability and low-latency/cost performance. Improved answer relevance at scale by moving from pure vector search to hybrid retrieval with metadata filtering and reranking, and partnered closely with healthcare operations/compliance to define acceptance criteria and human-in-the-loop guardrails.”
Mid-level Full-Stack Developer specializing in FinTech and Healthcare IT
“Candidate has hands-on experience at Cognizant building production-grade automation and integration solutions across Python ML services, Java microservices, Kafka, and Selenium-based UI testing. They stand out for a strong reliability mindset—covering failure modes, observability, flaky test hardening, and translating ambiguous payment-system business processes into resilient end-to-end automated workflows.”
Mid-level Full-Stack Engineer specializing in biomedical data platforms
“Backend engineer who has both shipped production systems at work and independently launched tab-review.com, a BI dashboard quality/linting platform. They combine pragmatic early-stage execution with strong instincts around scaling, observability, RBAC, and production reliability, and have also built internal AI-assisted reporting workflows using LangChain and human-in-the-loop review.”
Mid-level AI Engineer specializing in LLM, RAG, and multi-agent systems
Senior Platform/DevSecOps Engineer specializing in Kubernetes and secure cloud platforms
Mid-Level Software Engineer specializing in full-stack development and cloud platforms
Senior Full-Stack Software Engineer specializing in React and scalable web applications
Mid-level Software Engineer specializing in FinTech and scalable backend systems
Mid-Level Full-Stack Software Engineer specializing in Cloud, DevOps, and Platform Engineering
“Backend/Node.js-focused engineer who improved a widely used shared config/logging utility library by fixing a real-world async race condition (single disk read under concurrency) and adding stronger validation/testing, resulting in more deterministic services and faster startup/build/CI times. Also builds internal platform automation spanning Python/Go/TypeScript with strong documentation practices and security-conscious customer onboarding (e.g., sensitive Kubernetes clusters, HashiCorp Vault access issues).”
Mid-Level .NET Full-Stack Developer specializing in cloud-native web applications
“JavaScript engineer with open-source library contribution experience, including diagnosing a validation-related bug, shipping a tested fix, and improving documentation with practical examples and edge-case guidance to reduce repeated community questions. Emphasizes profiling-driven performance work, small safe refactors, and proactive ownership in fast-moving, unstructured teams.”
Mid-level Software Engineer specializing in full-stack web, Go microservices, and AI integrations
“Backend/LLM engineer who ships production internal tooling end-to-end: automated data-request processing with monitoring-driven improvements (better error diagnostics and lower latency via query/index tuning). Also built a RAG-based internal Q&A system over company docs and operational logs with guardrails (similarity thresholds, fallbacks, response limits) and an eval loop using real user queries and human review to drive prompt/retrieval changes.”