Vetted Integration Testing Professionals

“Backend/data engineer with strong authorization and compliance-domain experience: led a phased migration from a simplistic role model to modern RBAC on a Python serverless stack (Auth0 + AWS Lambda/API Gateway), coordinating changes across 5 repos with extensive manual and automated validation. Previously built and operated custom ETL pipelines (Airflow + Groovy/Java on Spark/YARN/Hadoop) to normalize messy customer email/chat/voice data for NLP-driven financial compliance indicators, including complex email journaling metadata enrichment and large-scale remediation reprocessing after production bugs.”

“Backend engineer with hands-on experience building Python/Flask microservices using PostgreSQL/SQLAlchemy, JWT auth, Docker, and GitHub Actions CI/CD. Strong in performance and scalability work—migrated heavy processing to Celery/Redis, tuned queries with EXPLAIN ANALYZE and indexing, and delivered 50%+ API latency reduction. Also integrates AI workflows (OpenAI APIs) with batching/caching/fallbacks and has implemented multi-tenant data isolation patterns.”

“Backend engineer with AWS multi-region production experience building APIs and workflow automation for data center/storage hardware operations (firmware orchestration, maintenance checks, ticketing, dashboards). Also shipped an internal AI chat tool that parses hardware runbooks and incorporates user feedback to retrain the model, and has a strong testing/quality discipline (95%+ coverage) plus database performance tuning via indexing and query monitoring.”

“Stripe engineer who shipped an end-to-end merchant fraud insights dashboard, spanning Spring Boot/Kafka risk-scoring services and a React+TypeScript UI. Focused on low-latency, high-volume transaction processing and production operations on AWS (EKS/CloudWatch), including handling a real traffic-spike latency incident via query optimization, indexing, and rate limiting.”

“Backend/distributed-systems engineer with Uber experience building real-time telemetry and safety signal pipelines. Strong in Kafka-based event-driven architectures, low-latency processing under peak load, and production reliability via monitoring, retries, and fallback logic; has Docker/Kubernetes and CI/CD deployment experience.”

“Full-stack engineer in the investment tracking/financial reporting space who built an automated reporting dashboard and compliance/reporting pipeline end-to-end using Next.js (App Router, server/client components), REST, and Postgres. Demonstrated measurable performance wins (~30% faster loads) through caching and query optimization, and built durable orchestrated workflows in n8n with retries, idempotency, and reconciliation checks.”

“Product-minded full-stack engineer who has owned customer-facing platforms end-to-end, including a unified web UI platform that increased adoption by 30% using feature flags and phased rollouts. Experienced designing TypeScript/React systems with microservices and RabbitMQ at scale, addressing reliability issues with DLQs, retries, and idempotent consumers, and building internal analytics tooling adopted company-wide within weeks.”

“LLM/RAG engineer who built a production-style multi-agent orchestrator for resume-to-recommendation workflows (PDF ingestion through screening and recommendations), emphasizing prompt tuning and strict JSON output contracts. Currently building a RAG application for an NGO using Airflow (DAGs + embeddings) and tackling messy, missing/imbalanced data; has hands-on retrieval stack experience (FAISS/HNSW, bge embeddings) and uses rigorous evaluation metrics for groundedness and hallucination control.”

“Backend engineer with experience at Meta and Accenture building regulated-data systems (healthcare/financial) using Python/Flask and Postgres. Has scaled high-throughput services to millions of daily requests, delivering measurable latency wins (~40% API latency reduction; ~35% faster DB-backed endpoints), and has productionized ML inference services using Docker/Kubernetes and AWS (ECS/SageMaker).”

“Backend owner at Apple for an AI workflow orchestration service, with hands-on experience stabilizing peak-traffic production systems using OpenTelemetry-style tracing, bounded async concurrency, and database performance tuning. Built and shipped a Python LLM-agent orchestration layer to automate multi-step operational workflows, emphasizing guardrails, auditability, and deterministic fallbacks to keep non-deterministic AI behavior production-safe.”

“Full-stack engineer with experience across Magna, C3.ai, and Amazon, building GenAI-enabled products and finance transaction systems. Has shipped Next.js (App Router) + TypeScript features backed by Go/Python RAG pipelines, and emphasizes production quality via load testing, Selenium regression coverage, LLM-aware integration testing, and Azure observability. Also built LangGraph-orchestrated multi-step content generation workflows with robust retry/idempotency strategies.”

“Meta engineer focused on reliability/operations tooling who built a unified real-time health dashboard and scalable telemetry pipelines (AWS + Datadog) for thousands of devices. Also shipped an internal LLM-powered knowledge assistant using RAG over wikis/runbooks/logs with strong guardrails and a rigorous eval loop that drove measurable accuracy improvements via automated doc ingestion and embedding updates.”

“Platform and distributed-systems leader (player-coach) who owned architecture and reliability for an Amazon analytics/data platform serving ~100K internal users at exabyte scale. Built an ML-driven “Lakeflow” optimization layer that cut pipeline completion times ~20–25% and reduced compute waste >15%, and led major incident response/redesign efforts (e.g., deletion storm) with strong rollout/observability/rollback practices.”

“Customer Success Services / Support professional working on Palantir Foundry who productionizes customer integrations (secure OAuth2, scheduled pipelines) and builds LLM-driven support automation (runbook matching) with monitoring and evaluation suites. Also leads developer workshops/demos on Foundry packaging/installation workflows, using live debugging techniques to make concepts concrete.”

“Software Developer at Amazon Robotics who co-developed a congestion-aware path planning system optimizing robot routes across 23 warehouses. Built and operated a real-time, service-integrated pipeline using AWS (AppConfig, DynamoDB), Java, and Redis caching, and has hands-on experience debugging robot behavior on-site with rigorous testing and staged releases.”

“Backend/platform engineer with hands-on ownership of Python services (Postgres/Redis/Celery) and measurable performance gains (~20–25%). Strong Kubernetes + ArgoCD GitOps experience delivering zero-downtime rollouts, plus led key reliability fixes (readiness probes, immutable tagging) and supported an on-prem to AWS migration using CDC replication and ALB traffic shifting; also built Kafka real-time analytics pipelines with schema registry.”

“Backend/data engineer with Optum healthcare claims domain experience building high-reliability Python microservices (FastAPI/Kafka/Postgres) and AWS data platforms (EKS, Glue, Redshift). Demonstrated strong production ownership: fixed duplicate Kafka processing via transactional outbox/idempotency, scaled to millions of daily events, and delivered major SQL performance gains (40+ min to <5 min, ~60% CPU reduction). Seeking remote-only work; targets $130k base.”

“Built and productionized a dual-agent LLM invoice-processing system for GFI Partners, adding guardrails and audit trails to earn stakeholder trust and drive adoption while cutting operational burden by 75%. Uses LangSmith observability to diagnose real-time workflow regressions and has experience teaching agentic AI concepts (e.g., at Carnegie Mellon) through hands-on, scaffolded demos.”

“Built production LLM systems focused on reliability and safety, including a plain-English deployment tool that generates validated plans and provisions to Kubernetes while preventing unsafe actions via schema enforcement and plan/execute separation. Also created multi-LLM workflows (LangGraph) and stakeholder-friendly demos at Bosch, including a PyQt/FastAPI/CUDA app comparing SAM2 vs SAMWISE for on-device object detection with intuitive UX for business users.”