Vetted Integration Testing Professionals

“Engineer with hands-on experience designing and leading multi-agent AI development workflows, including a LangGraph-based system that automated parts of a RAG pipeline and significantly reduced development time. Stands out for treating AI agents like an engineering team, with clear architecture, handoff schemas, validation, and supervisor-driven conflict resolution.”

“Functional/implementation consultant with experience across 10+ ERP deployments, including Infor LN and Salesforce/Rootstock, primarily in manufacturing environments. Brings hands-on ownership across the full lifecycle—from requirements, process mapping, configuration, and documentation through UAT, training, go-live, and hypercare—with particular depth in shop floor, procurement, inventory, and global operational complexity such as tax and shipping integrations.”

“Lead full stack Java developer with deep experience building compliance-sensitive government financial systems, including payment distribution, escrow hold management, reallocations, and disbursement workflows. Stands out for combining Angular/React frontend work with Spring Boot, Oracle SQL/PL-SQL, and batch/JMS architecture to stabilize high-volume transaction systems, automate manual workflows, and reduce production support issues.”

“Backend-focused engineer with strong Go and database optimization experience who improved a high-traffic API by about 30% and helped stabilize peak-load performance for an event reservation platform. Brings hands-on production experience across PostgreSQL, Redis, Rails/Go services, and B2B SaaS integrations with Slack, Hubstaff, and RingCentral, with a clear pattern of owning performance bottlenecks end to end.”

“Frontend engineer with experience redesigning high-stakes travel checkout flows at Spotnana and improving payment-page performance at RedViolet. Stands out for turning flight-specific, monolithic React code into reusable modular form architecture and delivering measurable UX gains like a 20% LCP improvement.”

“Backend/real-time systems engineer transitioning into robotics software: building ROS 2 fundamentals (pub/sub, custom messages, launch files) and experimenting with Nav2 + SLAM in Gazebo/RViz. Demonstrated practical debugging by tuning costmaps/planners and analyzing topic latency to stabilize simulated navigation, and has experience integrating telemetry pipelines and REST-based external interfaces.”

“Backend/microservices engineer (Java/Spring Boot, Kafka, Angular microfrontends) with Teradata experience building distributed analytics/query routing platforms and delivering 20–30% latency reductions through event-driven redesign and reliability hardening. Also built and shipped an end-to-end multimodal medical imaging AI feature (LLaVA/Mistral 7B + LoRA) with production guardrails like confidence-based human review, drift monitoring, and audit logs.”

“Backend engineer who built a real-time, event-driven alerting platform (Java/Spring Boot, Kafka, MongoDB) processing millions of events per day on AWS (Docker/Kubernetes), including hands-on performance debugging of Kafka consumer lag at peak. Also shipped an end-to-end LLM-based alert summarization feature and designed a multi-step incident triage agent workflow with retries and human-in-the-loop escalation.”

“Backend/integration-focused engineer in the Maryland area with production experience building FastAPI REST services secured with OAuth2.1/JWT and reliability patterns (timeouts, selective retries, idempotency, centralized error handling). Has delivered AWS-integrated MuleSoft/CloudHub solutions and supported AWS Glue ETL workflows, plus demonstrated strong SQL tuning with a 30–40s to 3–5s performance improvement.”

“Built and shipped a production RAG-based enterprise knowledge assistant to replace slow/inaccurate search across millions of documents, using LangChain orchestration with GPT-4/LLaMA and vector databases. Strong focus on production constraints—latency, hallucination control, and cost—using hybrid retrieval, guardrails, LLM-as-judge validation, and model routing, and has experience translating non-technical stakeholder pain points into measurable outcomes.”

“Software engineer/product owner experience at GE Healthcare, owning a patient records and claims workflow product end-to-end. Built React/TypeScript + Spring Boot systems with contract-driven APIs (OpenAPI) and operated Spring Boot microservices using RabbitMQ, focusing on reliability patterns (idempotency, DLQs) and performance improvements driven by clinical feedback. Also created an internal monitoring/deployment dashboard that became the default tool for on-call and production support.”

“Full-stack engineer and ML assistant in UC Irvine’s CS department who deployed a lab project showcase platform and integrated on-demand execution of computational projects using Docker for isolation. Also built and optimized Linux cloud/cluster test automation for research, diagnosing RAM and network sync bottlenecks, and later led development of a Python-based predictive analytics tool for musicians using probabilistic graphical models and flexible data pipelines.”

“Software engineer experienced in e-commerce systems, building customer-facing features and internal operations tools with TypeScript/React frontends and Spring Boot microservices. Demonstrated measurable performance wins (order-tracking API improved from ~2s to <700ms) and strong event-driven reliability practices with RabbitMQ (idempotency, DLQs, retry/backoff), including resolving a production queue backlog incident. Built an ops dashboard with real-time cross-service order tracing that became a daily tool for support/ops and reduced escalations to engineering.”

“Backend/AI engineer who built an AI icon-generation SaaS backend (Java/Spring Boot, MongoDB) on AWS, including async job processing with idempotency and S3-based result storage to handle traffic spikes. Also shipped applied AI in finance—an end-to-end fraud detection pipeline with risk scoring—and designed a banking support AI agent with strict guardrails, audit logs, and human-in-the-loop escalation.”

“Backend/platform engineer who owned a Python-based smart finance assistant backend, building async FastAPI microservices with PostgreSQL/Redis and deploying to AWS EKS via Docker/Helm and CI/CD (GitHub Actions, Jenkins). Strong in production reliability and migrations—implemented observability (Prometheus/Grafana), security (JWT RBAC), and executed a low-downtime monolith-to-microservices migration plus Kafka-based event streaming with ordering/retry/idempotency patterns.”

“AI/LLM engineer with production experience in legal tech: built a GPT-4 + LangChain RAG summarization system at Govpanel that reduced legal case-file review time by 50%+. Previously at LexisNexis, orchestrated end-to-end Airflow data/AI pipelines processing 5M+ legal documents daily, improving ETL runtime by 35% with robust validation, monitoring, and SLAs.”

“QA engineer with 11+ years (nearly 12) in IT across financial, healthcare, and telecommunications domains, experienced partnering closely with developers throughout Agile delivery. Strong in building/maintaining living test plans, running smoke/regression on new builds, and driving triage with impact-based prioritization using Jira/TestRail/Confluence; targets $100k+ base with standard benefits.”

“Full-stack/backend engineer with deep insurance claims domain experience who built and operated a microservices + ETL platform (Java/Spring Boot + Python + Kafka/Databricks) processing 1M+ daily transactions. Combines production-grade reliability (99.7% uptime, zero-downtime blue/green releases, strong observability) with customer-facing UI delivery (AngularJS/React+TS dashboards and a hackathon-winning research chatbot).”

“System Engineer with Panasonic Avionics and DIRECTV experience who functions as a software integration focal point, owning system-level QA from requirements and ATP verification through regression and release readiness. Brings rigorous, compliance-driven testing (FAA/ISO) plus strong RCA skills, including reproducing critical UI freezes under high memory conditions and supplying logs/memory dumps to drive engineering fixes.”

“QA automation engineer with hands-on ownership of Selenium (C#) and Cypress (JavaScript) suites, including CI integration in GitLab with PR smoke gating and nightly regressions with JUnit reports/screenshots. Drove a reported ~60% reduction in manual effort, improved suite maintainability through reuse/merging tests, and proactively shaped requirements/acceptance criteria in sprint planning to prevent defects (including claims calculation and server/log-related issues).”

“Full-stack engineer (4+ years) with Citigroup experience building a modular banking dashboard using React/TypeScript/Redux and a Java Spring Boot microservices backend (12+ services) integrated with Kafka. Strong in reliability/observability and cloud operations on AWS (EC2/S3/Lambda, CloudWatch, Prometheus, ELK, IaC with Terraform/CloudFormation), with quantified improvements in latency, development speed, and data pipeline correctness.”

“Software engineer with Prudential Financial experience building enterprise Spring Boot microservices for policy/risk assessment, including integrating Python ML models via Flask and hardening services with resiliency patterns. Also led an AWS lift-and-shift modernization during an internship (EC2/ELB/Route53/Auto Scaling) and built a personal diffusion-model text-to-music project using BERT tokens mapped to Mel spectrograms.”

“Full-stack engineer from HPE GreenLake who built and owned a cloud/hypervisor resource management experience end-to-end, including Postgres modeling, typed REST/GraphQL integrations, and resilient provisioning workflows. Drove a centralized Redux-based UI architecture that boosted dev velocity by 50% across 30+ teams, and continued post-launch ownership with DR integrations (AWS/GCP/Azure) plus expanded Cypress testing and observability.”

“Worked on a long-running, high-dependency production rollout in financial post-trade systems, delivering trade-booking functionality on post-trade feeds used by multiple downstream teams. Emphasizes cross-team/external-team coordination and extensive testing to avoid disruptions, with additional experience improving application reliability via VPN-based resiliency measures.”