Vetted AWS Professionals

“Embedded/software candidate who built an arcade-style game on a PSoC6 ARM microcontroller using FreeRTOS and custom peripheral/protocol drivers, ultimately completing the project as the sole developer. Also brings strong systems tooling exposure (Docker-heavy coursework, Kubernetes familiarity) plus internship experience at Accenture working with CI/CD-based validation and debugging in a client environment.”

“Backend engineer with hands-on ownership of FastAPI/Django services using MongoDB and React integration, focused on production reliability and performance (Redis caching, Celery background jobs, automated testing). Has delivered AWS container deployments via GitHub Actions to ECR with scripted rollouts/health checks, and supported phased migrations with replication and rollback planning. Also built a real-time user-activity streaming pipeline addressing partition hot spots and consumer lag through partition-key strategy, idempotency, and monitoring.”

“JavaScript/Node.js engineer with open-source contribution experience (Mongoose) focused on connection pooling, test reliability, and memory/resource management. Has diagnosed and fixed real-world performance issues in an insurance claims application and improved resilience via failover DB design. Also experienced producing compliance/governance documentation for an EU-based biopharma, enabling stakeholders to make decisions quickly amid changing regulations.”

“Software engineer with experience delivering customer-facing and internal tools across GE Renewables, GE Healthcare (supply chain/production systems), and a Boulder-based event app startup. Recently focused on scaling backend performance using Redis and RabbitMQ, and has hands-on experience resolving hard-to-reproduce production issues in legacy authentication/session systems; also deployed a personal project (Journal Buddy) publicly.”

“Built and productionized an agentic LLM workflow during a summer internship to transform unstructured clinical reports into analytics-ready structured data, using a LangChain multi-agent design plus an LLM-as-a-judge layer to control quality in a regulated setting. Also has experience orchestrating ML pipelines at Piramal Capital using AWS Step Functions/EventBridge/CloudWatch, with strong emphasis on observability, evaluation rigor, and measurable impact (80–90% reduction in manual data entry).”

“Engineering/technology leader (CTO-style) with experience scaling orgs and running distributed teams across four continents for over a decade. Led a high-stakes modernization of a securities trading platform at Wedbush—migrating from monolith to microservices on AWS with zero-downtime constraints—driving 45% execution performance improvement and enabling 25% market share growth. Emphasizes business-aligned roadmaps, build-vs-buy rigor, and scalable engineering practices/culture.”

“Backend-leaning full-stack engineer who ships AI-enabled products end-to-end: built CodeChat, a production internal codebase Q&A tool using RAG with Pinecone and a model-agnostic wrapper across OpenAI/Anthropic/AWS Bedrock, cutting AWS costs ~50% and latency ~45%. Also built and operated RealityStream, a Flask-based real-time forecasting API with JWT/RBAC, MLflow model versioning, and Prometheus/Grafana observability, including handling a real production latency incident via rollback, preloading, and caching.”

“QA automation engineer who owned an end-to-end automated regression suite for a PlayStation digital store flow (login through checkout/payment), building a hybrid POM/data-driven framework from scratch with Selenium/TestNG/Cucumber and also using Playwright/TypeScript and Cypress. Integrated the suite into Jenkins CI/CD with nightly runs and reporting, improved coverage (happy + negative paths), and reduced release risk by catching critical issues like session timeout and transaction/payment defects before production.”

“Product-focused full-stack engineer who built and shipped an LLM-powered document-to-flashcard conversion pipeline end-to-end (backend + React/TypeScript UI) in ~10 days. Experienced with event-driven queue/worker systems (Redis/BullMQ), PostgreSQL performance tuning, and AWS production operations, including resolving real scaling incidents and driving reliability from ~70% to nearly 100%.”

“Full-stack engineer with early-stage startup experience who shipped and owned production Next.js (App Router + TypeScript) features end-to-end, including auth-aware APIs, caching, and post-launch monitoring/iteration. Demonstrates strong performance and reliability chops across React UX optimization, Postgres analytics modeling/query tuning (validated via query plans), and durable ingestion workflows with retries/idempotency.”

“IBM Power/AIX infrastructure engineer who has owned a large AIX 7.x/VIOS/HMC estate (hundreds of LPARs), handling provisioning, patching, tuning, and incident response. Demonstrated high-availability and recovery leadership with PowerHA failovers and SAN-path RCA/resiliency improvements, plus successful AIX 7.1→7.3 migrations with minimal downtime/no data loss. Also brings modern DevOps/IaC experience (Jenkins + Vault, Docker/Kubernetes, Terraform on Azure) with a focus on secure, repeatable deployments and drift control.”

“QA engineer with Citibank experience owning mobile automation and cross-platform validation (Android/iOS), including push notifications, RBAC, and backend API/data sync checks. Demonstrates strong Cypress/JavaScript E2E expertise—stabilizing CI-flaky React tests via cy.intercept—and builds pragmatic GitLab CI pipelines with smoke/regression gating plus rich reporting (Cypress Dashboard, Slack).”

“Engineer with Deloitte experience building real-time analytics products and scalable Kafka/Go/Postgres pipelines, plus production LLM features using RAG and embeddings. Demonstrates strong focus on performance, reliability, and guardrails/evaluation loops to reduce hallucinations and improve real-world AI system quality.”

“Early engineer at a fast-growing startup who owned an AI-powered portfolio/site generation workflow end-to-end (frontend in Next.js App Router/TypeScript through backend orchestration). Emphasizes server-first security/performance (Server Components/Actions, revalidation), and production hardening with validation, caching, observability, retries/idempotency, and CI/E2E testing.”

“Former co-founder at PreConception (acquired) who partnered closely with Operations, Legal, and Medical teams to deliver a HIPAA-compliant product meeting technical and regulatory requirements. Motivated by mission and team fit, and interested in a Venture Studio CTO path with a focus on 0-to-1 building and early validation via beta testing/PMF.”

“Backend/full-stack engineer from Foxconn Industrial Internet who led development of a production TypeScript/Node.js facility monitoring platform delivering near real-time manufacturing metrics (e.g., downtime and OEE) using MySQL + InfluxDB and a React dashboard. Demonstrates strong production operations mindset with queue-based workers, idempotency/DLQ patterns, structured observability, and automated Docker + GitLab CI/CD deployments.”

“Financial data engineer who has built and operated high-volume batch + streaming pipelines (200–300 GB/day; 5–10k events/sec) using AWS, Spark/Delta, Airflow, Kafka, and Snowflake, with strong emphasis on data quality and reliability. Demonstrated measurable impact via 99.9% SLA adherence, major reductions in bad records/nulls, MTTR improvements, and significant latency/runtime/query performance gains; also built a distributed web-scraping system processing 5–10M records/day with anti-bot and schema-drift defenses.”

“Built and launched a personalized sprint-planning dashboard to reduce recurring planning friction, choosing a simple, reliable scoring approach over a complex model. Iterated based on team feedback (more control, dependency clarity, performance), achieving a reported 20% drop in task spillovers; transparent about not yet shipping production LLM/RAG features but actively learning.”

“Data engineer with Cigna experience building and operating an end-to-end AWS-based healthcare claims pipeline processing ~2TB/day, using Glue/Kafka/PySpark/SQL into Redshift. Strong focus on data quality and reliability (schema validation, monitoring/alerting, retries/checkpointing/backfills), reporting improved accuracy (~99%) and reduced latency, plus experience serving real-time Kafka/Spark data to downstream analytics with documented data contracts.”

“Built and shipped production RAG-based LLM agents automating multi-step document query workflows, emphasizing reliability via monitoring, retries, structured exception handling, and fallback retrieval (alternative embeddings/keyword search). Demonstrated measurable gains (18% latency improvement, 25% retrieval efficiency, 12% precision) and has experience integrating agents with messy tax and transaction data at RSM using validation/cleaning and idempotent design.”

“Data engineer/backend data services builder with end-to-end ownership of production pipelines for a Pfizer client, combining Python/SQL ingestion and transformation with strong data quality controls. Delivered measurable performance gains (~30% faster queries) and improved reliability through monitoring/alerting (Splunk, Prometheus/Grafana), structured logging, and incident response; also built internal REST APIs with versioning and caching and set up GitLab-based CI/CD with containerized deployments.”

“Data engineer focused on AWS + Spark/Databricks pipelines, including an end-to-end nightly loan-data ingestion flow (~2.2M records) from Postgres/S3 through Glue and Databricks into a DWH with layered validation and alerting. Also built real-time streaming with Kafka + Spark Structured Streaming and a master’s project streaming Reddit data for sentiment analysis under ambiguous requirements and tight budget constraints.”

“Full-stack React/Next.js engineer focused on routing and data-fetching reliability, including handling slow/unreliable networks with loading states, retries, and request cancellation to prevent stale data. Has delivered measurable frontend performance gains (reported ~40% improvement in time-to-interactive) using lazy loading, memoization, and profiling with React Profiler.”