Vetted Confluence Professionals

“Backend engineer focused on Python/FastAPI microservices running on Kubernetes (AWS EKS) with strong GitOps/CI/CD ownership (GitHub Actions + ArgoCD). Demonstrated measurable performance wins (p95 latency cut from >1s to <200ms) and production reliability work across Kafka/Redis streaming and cloud-to-on-prem migrations (RDS/S3 to Postgres/MinIO) using parallel validation and checksum-based consistency checks.”

“Full-stack engineer with strong data engineering and privacy-domain experience, having owned an automated Data Subject Rights (DSR) processing pipeline end-to-end across Azure SQL and GCP (GCS/BigQuery). Emphasizes production reliability via idempotency, validation checkpoints, structured logging/monitoring, and safe CI/CD-driven deployments, and has also built React+TypeScript + Node/Postgres web apps with scalable, maintainable architecture.”

“Full-stack engineer (SAP Labs experience) who built an end-to-end, real-time fraud detection system on Java 11/Spring Boot microservices with Kafka event streaming and a React/Redux analytics dashboard with WebSocket updates. Demonstrated strong production ownership by diagnosing a critical memory leak with Prometheus/CloudWatch + heap dumps and improving performance with Redis caching (40% faster queries), while also modernizing deployments via Kubernetes, Jenkins CI/CD, and Terraform.”

“Backend/data engineer from Oliver Wyman who built and ran production Python (FastAPI) services on AWS (ECS/Lambda/API Gateway) supporting risk modeling and regulatory reporting. Strong in reliability/observability, Glue-based ETL with data quality controls, and legacy SAS-to-Python modernization with rigorous parity validation; also demonstrated measurable SQL performance wins and cost-control improvements in serverless scaling. Based in Raleigh, NC and can travel onsite for important Bethesda-area meetings.”

“Full-stack engineer who has owned customer-facing AI recommendation and analytics dashboards end-to-end (backend APIs/data processing through React UI, deployment, and monitoring). Demonstrates strong systems thinking around scaling microservices—using observability, caching, async workflows, and resilience patterns—and also built an internal ops dashboard that became the default tool for on-call incident reviews.”

“At Triple Whale, partnered with product, engineering, and sales to bring enterprise LLM-based budget recommendation agents from impressive prototypes to trusted production workflows. Strong in prompt/input tuning, explainable structured outputs, and running tightly-scoped POCs with clear success criteria—plus hands-on technical demos and post-sale implementation to drive adoption.”

“Built production LLM automations using the Claude API, including a sales enablement workflow that summarizes playbooks and incorporates sales call metadata into strategic one-pagers. Experienced in orchestrating and scheduling data pipelines with SnapLogic, Airflow, and Databricks, and in scaling LLM API calls via parallel/batch processing. Also partnered with HR to deliver prompt-tuned, automated Slack messaging aligned to business tone and acceptance criteria.”

“Built and shipped a real-time oncology risk prediction system used by doctors during patient visits, trained on clinical data in AWS SageMaker and deployed via FastAPI with sub-second responses. Emphasizes clinician-trust features (SHAP explainability, validation checks) and HIPAA-compliant controls (encryption, RBAC, audit logging), plus Kubernetes-based production operations with autoscaling, monitoring, and drift/retraining workflows; collaborated closely with oncologists at Flatiron Health.”

“Game QA professional who shipped AAA (Overwatch 2) as quality feature owner for Campaign missions, owning high-risk areas like mission progression stability and preventing soft-lock/state desync issues. Also shipped Stormgate and caught a critical Steam achievement integration failure near RC by recreating the issue in an anti-cheat, live-mirroring environment and driving it through fix + regression verification.”

“Software engineer with strong compliance-domain experience who built a customer-facing compliance and reporting dashboard using React/TypeScript with Spring Boot microservices. Demonstrates mature production engineering practices—contract-first APIs, event-driven architecture (Kafka/RabbitMQ), caching (Redis), and robust CI/CD + observability (Prometheus/Grafana/ELK)—and also created a Python-based audit automation tool adopted into the standard release process.”

“Product-focused full-stack engineer with Walmart and Dell experience who built and shipped a real-time engagement dashboard end-to-end (Kafka Streams, Spring Boot, React/TypeScript/D3) used daily by business teams, moving them from next-day reports to real-time decisioning. Strong in performance/reliability (Redis caching cut latency ~40%, 90%+ test coverage, Prometheus/CloudWatch monitoring) and production operations on AWS/EKS including handling a cascading failure from a memory leak with zero-downtime rollback and redeploy.”

“iOS player-coach who led end-to-end development of real-time customer support chat and unified notification systems for T-Mobile’s iOS app using SwiftUI, Firebase, WebSockets, and Core Data (including offline handling). Drove measurable reliability/latency gains (~30%) through a major notification refactor and owned a high-severity push-notification incident from rollback through RCA and backward-compatible hotfix, while also scaling team process and people management.”

“Infrastructure/Unix engineer with production PowerHA/HACMP operations experience (resource groups, service IPs, shared storage) who has executed planned failovers and recovered a real outage involving a SAN driver crash and manual Oracle recovery (restored service in ~15 minutes with zero data loss). Also supports cloud DevOps practices including CI/CD security scanning (SonarQube, Snyk), container registry/versioning, and Terraform Cloud-based IaC across AWS and GCP with PR/Jenkins-driven plan-and-apply workflows.”

“Former PwC Director with hands-on early-stage venture experience (e.g., BridgeLights, a big-data analytics concept for early fintech) spanning concept creation, platform architecture, and go-to-market experimentation. Strong focus on building scalable, modular data platforms with rigorous governance/compliance (data lineage, quality controls) and supporting technical diligence in investor-aligned environments.”

“Software engineer with experience across enterprise (AIG, MSCI) and an early-stage startup (Job Map), owning production systems end-to-end. Built secure insurance microservices on Spring Boot with JWT/RBAC and AWS-based CI/CD/observability, plus Kafka streaming pipelines for financial data. Also shipped a GenAI personalization MVP using FastAPI and LLM APIs in a high-ambiguity startup environment.”

“Python/AWS engineer focused on batch-processing and data workflows, including building reusable S3/boto3 utilities with reliability features and IAM-based auth. Has led low-risk legacy modernizations using parity testing plus a month of parallel production runs, and has owned production issues end-to-end (including fixing a client-side Excel macro) while contributing to significant AWS cost reductions (~$10k/month).”

“Built and deployed a production LLM/RAG document automation system for business documents (contracts/claim forms) that extracts schema-validated JSON, generates grounded summaries/Q&A, and integrates into transaction systems via APIs. Emphasizes real-world reliability: hallucination controls, layout-aware parsing with OCR fallback, Step Functions-orchestrated workflows with retries/timeouts, and human-in-the-loop review designed in close partnership with operations and claims stakeholders.”

“AI/ML full-stack practitioner in a small-scale manufacturing/lab operations environment who deployed a production ML system to improve blood cell order fulfillment by predicting yield/success from donor characteristics. Experienced building custom multi-agent orchestration (Python, LangChain/LangGraph, MCP) and balancing reliability, data quality constraints, and token/ROI economics while communicating tradeoffs to VP-level business stakeholders.”

“Enterprise platform engineer/product owner who led end-to-end delivery of customer-facing ServiceNow Service Catalog/workflow solutions, emphasizing reliability, security, and fast iteration. Built React/TypeScript portals with Node.js and Spring Boot backends, and improved microservices reliability at scale using Kafka, monitoring, and robust retry/timeout patterns.”

“Frontend-focused engineer with experience building and optimizing React-based dashboards and reusable component libraries in a multi-team, internal open-source-style environment at Merck (ClearSight Forecasting Dashboard). Also handled production user issues on a live streaming platform (GameSee.tv) and built a financial application from scratch at Manipal Business Solutions, owning backend services, middle-tier APIs, and third-party integrations.”

“Procurement/sourcing professional with hands-on experience selecting and rolling out an analytics dashboard vendor end-to-end—using stakeholder discovery, POCs, and a scoring matrix—then negotiating a ~26% cost reduction and waiving implementation fees. Also demonstrates strong trade compliance instincts by catching and correcting an incorrect tariff code that would have increased duties ~18%, and uses structured milestone/risk tracking (RAG) to keep OTD and approvals on track.”

“AI/ML engineer with HP experience building and productionizing an LLM-powered document intelligence platform (LangChain + Pinecone) to deliver semantic search and contextual Q&A across millions of enterprise support documents. Demonstrates strong MLOps and scaling expertise (Airflow, Kubernetes autoscaling, Triton GPU inference, monitoring with Prometheus/W&B) plus a structured approach to evaluation (A/B tests, shadow deployments, failover) and effective collaboration with non-technical stakeholders.”

“Backend/platform engineer from Fanatics sportsbook core team with deep experience in real-time ingestion systems (Kafka) and high-throughput performance optimization. Delivered an 87% latency reduction on a Java API handling hundreds of thousands of updates per second, and improved reliability of shared internal libraries via deterministic recovery logic, strong testing, and feature-flagged rollouts.”