Pre-screened and vetted.
Senior Full-Stack Software Engineer specializing in Frontend (React/JavaScript)
“Frontend-focused engineer with full-stack experience who modernized a legacy HR platform (CoffeeScript/Marionette) by migrating key UIs to React/Redux and adding TypeScript for robustness. Built an internal client monitoring tool end-to-end with a microservices-oriented approach and strong testing practices (Jest/Selenium), and also led a major GraphQL v1→v2 migration delivered incrementally over ~6 weeks while optimizing Django/MySQL/DynamoDB performance.”
Mid-level Full-Stack Python Developer & Data Engineer specializing in ETL and web platforms
“Backend engineer who led major modernization efforts at GoDaddy, migrating legacy Perl services to Python/FastAPI with an incremental rollout strategy, containerization (Docker/Kubernetes), and CI/CD (Jenkins/GitHub Actions). Strong focus on secure, reliable API design (JWT, RBAC, PostgreSQL row-level security), rigorous testing, and data integrity—plus experience hardening an automated web-scraping pipeline against changing site structures and downtime.”
Director of Customer Success specializing in enterprise SaaS implementations and AI platforms
“Enterprise CSM/program lead specializing in AI-powered search and workflow automation, who owned an end-to-end generative AI chatbot rollout that replaced manual Excel-based RFP processes and achieved 4.5/5 CSAT. Leveraged outcomes to expand the account into two additional use cases (tripling ARR) and has a track record of influencing product priorities (UI personalization) and driving Voice AI expansions tied to operational support workflows.”
Mid-level QA Engineer specializing in manual, mobile, and API testing
“QA automation engineer who owned end-to-end test automation for a web-based enterprise application, building and scaling suites in Selenium/Java/TestNG and Cypress/JavaScript. Strong in CI/CD integration with PR gating and actionable reporting, and has prevented high-severity auth/session regressions by catching role-based login/token issues early via automated CI runs.”
Executive Engineering Leader specializing in SaaS, FinTech, and AI
“Startup-oriented product/technology leader targeting CTO roles, with experience evaluating and scoping high-impact product expansions. At Crelate, helped assess and shape a contract timekeeping/invoicing initiative that expanded TAM by hundreds of millions and increased ACV 2-3x, contributing to successful market traction and the company’s path to Series C.”
Senior Full-Stack Java Engineer specializing in cloud-native microservices
“Backend engineer with experience at Visa and Ansel, owning cloud-native, event-driven microservices end-to-end in high-volume and business-critical environments. Stands out for combining scalable Java/Spring/Kafka architecture with strong production rigor, incident ownership, and a pragmatic approach to AI workflow integration that emphasizes guardrails over blind model trust.”
Mid-level Full-Stack Developer specializing in cloud-native enterprise platforms
“Built Nexthire-AI, shipping an end-to-end LLM-powered resume–job description matching product (React + Node.js) using embeddings and retrieval to generate match scores and skill-gap recommendations. Improved post-launch engagement by making feedback cleaner and more actionable, and added production guardrails (validation, timeouts, fallbacks) to handle messy resume formats and AI API instability.”
Mid-level Software Engineer specializing in backend systems and cloud-native microservices
“Engineer with a process-driven approach to AI-assisted software development, focused on orchestrating where AI adds value while maintaining human review and verification. Has applied this in backend work such as an S3-based invoice pipeline and used multi-agent workflows to speed up large API refactors across many endpoints.”
Mid-level Software Developer specializing in full-stack enterprise applications
“Software engineer with experience building and iterating high-volume Spring Boot microservices on AWS (Docker/Kubernetes) and integrating with React front-ends. Also delivered an LLM-powered document summarization system using embeddings + retrieval (RAG) with grounding/guardrails and built evaluation loops that directly drove retrieval and chunking improvements. Has scaled Kafka-based pipelines processing millions of messy financial/infrastructure records with reliability and cost/latency tradeoff management.”
Senior Software Engineer specializing in backend microservices, cloud, and full-stack systems
“Backend/platform engineer who has built and scaled production Java/Spring Boot + Kafka services on AWS/Kubernetes (1M+ msgs/day) and led reliability/performance fixes that restored SLAs (25–30% latency improvement; 99.9% uptime). Also shipped an AI customer-support chatbot end-to-end using retrieval + guardrails and rigorous evaluation/observability, improving resolution time 40% and satisfaction 25%, with a strong plan/execute/verify approach to agentic workflow reliability.”
Entry-Level Software Engineer specializing in full-stack development and machine learning
“Master’s CS candidate with backend internship experience modernizing live operational workflows at NatWest/NetWess, focusing on reliability improvements, safer CI/CD deployments, and incremental refactors using feature flags and rollback paths. Built FastAPI-based APIs with strong security patterns (JWT + 2FA/TOTP, centralized authorization, RLS) and demonstrated attention to edge cases like idempotency and data consistency in a Netflix-clone project.”
Mid-Level Software Engineer specializing in FinTech microservices and AI automation
“Backend engineer with experience evolving a real-time transaction and rewards processing platform from a tightly coupled architecture into domain-based microservices. Uses REST plus Kafka for synchronous vs. asynchronous workflows, and builds Python/FastAPI APIs with Pydantic contracts, Docker/Kubernetes deployments, and JWT/OAuth-based security; has also supported analytics/dashboard use cases (Power BI).”
Mid-level Full-Stack Java Developer specializing in microservices on AWS
“Frontend-focused engineer who built a reusable React component library (documented in Storybook) to standardize and speed up UI development across teams at Ikea, including a configurable, high-performance order list component. Also demonstrated end-to-end ownership in an unstructured environment at First Citizens Bank by defining API contracts and delivering backend services with caching and monitoring.”
Mid-level Full-Stack Software Engineer specializing in cloud-native microservices and AI integrations
“Backend engineer who has delivered large, measurable performance wins (10x throughput, 67% latency reduction) by combining Flask microservices, Redis caching, and AWS autoscaling/observability. Has hands-on depth in SQLAlchemy/Postgres optimization and production scaling pitfalls (cache consistency, connection exhaustion), plus experience deploying real-time ML inference (XGBoost) on AWS Lambda and building secure multi-tenant Kubernetes isolation.”
Mid-level Full-Stack Java Developer specializing in cloud-native microservices
“Full-stack Java developer with IBM and Epic Systems experience modernizing legacy enterprise apps into microservices and delivering customer-facing healthcare claims workflows at very high scale (2M+ transactions/day). Strong blend of product engineering (APIs + React/TypeScript UI) and production operations on AWS, including performance incident remediation via query optimization, indexing, and autoscaling.”
Mid-level QA Analyst specializing in manual, automation, API, and backend testing
“QA engineer with 4+ years testing UX/UI for enterprise, data-driven and legacy platforms (including Dell Technologies), partnering closely with developers/product/business through Agile sprints. Experienced validating end-to-end behavior across UI, REST APIs (Postman), and databases (SQL), and automating regression with Selenium Java/TestNG. Notable work includes diagnosing search ranking/pagination issues by correlating UI behavior with API responses and metadata consistency.”
Senior QA Automation Engineer (SDET) specializing in healthcare and financial services testing
“QA Automation Engineer with 7+ years building dependable enterprise automation suites across UI, API, and database layers using Selenium (Java), Playwright, Karate, and Cypress. Integrates smoke/regression suites into CI/CD (GitLab/Jenkins/GitHub Actions) with reporting and notifications, and has prevented production issues by catching silent backend failures and high-impact payment defects through end-to-end validation and strong root-cause evidence.”
Mid-Level Backend Software Engineer specializing in Java/Spring microservices and AWS
“Backend-focused engineer with production experience building Spring Boot services for automated workflow and data-processing platforms, using queues plus retry and idempotency patterns. Also uses Python to automate data processing; emphasizes testing and peer review for maintainability.”
Senior Full-Stack Java Developer specializing in cloud-native microservices
“Backend/platform engineer with production ownership of high-volume transaction analytics and fraud monitoring services built in Java/Spring Boot. Has scaled data processing platforms (including healthcare datasets) and operated Kafka-based event pipelines with schema versioning, deduplication, and replay/backfill workflows, using strong observability via CloudWatch/Grafana and CI/CD with Jenkins.”
Mid-level Full-Stack Software Engineer specializing in AI platforms and cloud microservices
“Distributed-systems engineer applying robotics-style patterns to software: built "Vibecheck," a high-throughput real-time video + OS-telemetry fusion and analysis system (500+ MB/session) with strict latency constraints. Strong in containerization and CI/CD (Docker, GitHub Actions) and in designing fault-tolerant, event-driven architectures (Kafka/RabbitMQ), plus hands-on debugging of multi-agent coordination using blackboard + watchdog/circuit-breaker control patterns.”
Senior ML Engineer & Data Scientist specializing in LLM agents, retrieval/ranking, and MLOps
“Machine Learning Engineer currently at Webster Bank building an enterprise-scale LLM agent for Temenos Journey Manager/Maestro, using RAG-style multi-stage retrieval with FAISS/Pinecone, hybrid dense+sparse search, and LoRA fine-tuning optimized via NDCG/MAP and A/B testing. Previously handled messy incident/telemetry data at Deuta Werke GmbH with deterministic + fuzzy entity resolution, and has strong production data engineering experience across Spark/Hadoop and Python ETL systems.”
Senior Software Engineer specializing in AI, cloud infrastructure, and full-stack development
“ML/NLP engineer who built a production system that converts large-scale unstructured text into a connected, searchable knowledge base using spaCy + Sentence Transformers/FAISS and a Neo4j knowledge graph, with BERTopic and XGBoost for organization/labeling. Strong focus on production-grade Python workflows (FastAPI/Celery, Pydantic validation, Docker, AWS ECS/Lambda) and robust entity resolution with measurable precision/recall and human review for low-confidence matches.”
Mid-level Full-Stack Developer specializing in cloud-native Java/React microservices
“Backend/DevOps-focused engineer with hands-on ownership of Java Spring Boot microservices on AWS, including Kubernetes deployments, Jenkins-based CI/CD, and GitOps-driven infrastructure-as-code (Terraform/Helm). Delivered measurable performance gains (25% faster APIs) and built a Kafka real-time streaming pipeline with strong observability (Prometheus/Grafana/CloudWatch) and rapid rollback practices that cut production downtime from hours to minutes.”
Mid-level Data Engineer specializing in real-time pipelines and cloud data platforms
“Backend engineer with hands-on experience building secure Python/Flask services (sessions, JWT, RBAC) and optimizing PostgreSQL/SQLAlchemy performance, including custom SQL using CTEs/window functions profiled via EXPLAIN ANALYZE. Also integrates LLM features via OpenAI/Azure into backend systems and improves scalability with RabbitMQ-driven async processing, caching, and multi-tenant data isolation patterns.”