Vetted Confluence Professionals

“Tesla sourcing/supplier readiness professional focused on critical lithium-ion battery components, owning end-to-end supplier onboarding and delivery execution. Uses SQL and Power BI to run integrated readiness plans across samples/approvals/tooling and proactively mitigates cost and import-duty risks while improving supplier performance through structured execution cadences.”

“Co-founded a Digital Loss Prevention (DLP) startup and raised $6M in seed funding by showcasing a controlled, laptop-based technology demo. Post-funding, drove MVP planning and execution by sequencing operations and assembling a team to build an appliance MVP, using an iterative build/evaluate/visualize approach.”

“Operations/strategy leader who owned a founder-level turnaround at Bolt Threads, rescuing and scaling a failing business unit through ERP + S&OP implementation, operating model redesign, and cross-functional KPI-driven execution. Achieved a 97% COGS reduction, enabled repeatable production at scale, and supported investor diligence and SPAC readiness by creating a credible operating narrative.”

“Amazon Fire TV Devices engineer who built and shipped a production LLM-powered lab triage and validation system that grounds recommendations in internal runbooks/known-issue data and pushes evidence-based actions via dashboards and Slack. Emphasizes safety and measurability with structured JSON outputs, replay-based evaluation on historical incidents, and production metrics (e.g., disagreement rate and time-to-first-action), plus cost/latency optimizations like caching, batching, and rule-based fast paths.”

“Robotics software engineer focused on production-grade autonomy in GPS-denied environments, building full navigation stacks (perception, EKF/UKF sensor fusion, planning, control) in ROS2. Integrated YOLOv8/semantic segmentation/RL policies into real-time NAV2 pipelines via a custom perception-aware costmap layer, with emphasis on deterministic control loops, embedded GPU performance, and robust system observability/fault tolerance.”

“React-focused engineer who built a full-stack analytics/test-metrics dashboard (React frontend + Python backend) and turned common UI pieces (data tables, filter panels, chart wrappers) into a reusable internal component library with docs, examples, and basic tests. Strong on profiling-driven performance optimization (React Profiler, memoization) and on owning ambiguous internal-tool projects end-to-end; now planning to package internal patterns into public open-source components.”

Scott Compton

Screened

Staff/Lead Game Systems Designer specializing in AAA live games and emergent narrative

30y exp

“Progression/economy designer and lead live designer with shipped AAA and live-service experience across Shadow of Mordor/War, Guardians of Middle-earth, Days Gone, and Star Trek Online. Known for building quantitative tuning models (200+ stat points calculator), leading large QA-driven balance loops, and using telemetry to uncover and fix major friction points (e.g., off-screen archer deaths) while maintaining engaging, fair progression.”

Anu Baluguri

Screened

Mid-Level Software Engineer specializing in cloud-native microservices and event-driven systems

San Francisco, CA4y exp

“Full-stack engineer with production experience at Atlassian and Zoho, spanning GraphQL federation, React/TypeScript frontends, and cloud-native AWS/Kubernetes operations. Built and operated a federated GraphQL gateway with Terraform + CI/CD + observability, delivering major latency and integration-time improvements, and also designed high-volume Kafka data pipelines (10M+ events/day) with strong reliability guarantees.”

Ranganayak Meravath

Screened

Mid-level Generative AI Engineer specializing in RAG, agentic copilots, and regulated AI

5y exp

“Senior engineer who built and productionized an Azure-based Enterprise AI Copilot for financial/compliance teams, focused on grounded, auditable answers with citations to reduce hallucinations in regulated workflows. Experienced designing multi-step agent orchestration and improving reliability through targeted iterations (e.g., fixing chunking/parsing to materially improve citation accuracy), plus building defensive pipelines for messy ERP/operational finance data.”

“Product leader with experience at Chegg building student-focused education products, including an ebook subscription launched in response to Amazon competition that helped drive major digital growth. Also led integration of AI/ML capabilities for question classification and personalized learning workflows, with a strong emphasis on accuracy, affordability, and acting on student feedback.”

Melbourne Brown

Screened

Senior Software Engineer specializing in AI-driven cloud-native platforms

Atlanta, GA12y exp

“Engineer with unusual breadth: from a tiny startup building racehorse medical-record systems on credit-card chips for live racetrack demos to modern AI-powered contract intelligence platforms in production. Brings hands-on full-stack and backend depth across React, Python, .NET, PostgreSQL, Kubernetes, and Azure, with a track record of making complex, reliability-sensitive systems work in real-world conditions.”

“Built and deployed a production healthcare medical review agent that automates call-transcript summarization and medication reconciliation using a hybrid deterministic + LangGraph-orchestrated LLM workflow. Demonstrates strong reliability engineering (guardrails, schema validation, confidence thresholds, golden/adversarial eval, Langfuse monitoring) in a regulated environment, delivering 60% lower latency and 70%+ efficiency gains while partnering closely with care managers and operations.”

“Full-stack engineer (~4 years) who has owned and shipped customer-facing SaaS onboarding and a role-based real-time analytics dashboard using TypeScript/React with a modular backend. Experienced in microservices with RabbitMQ and strong observability practices (correlation IDs, structured logging, queue metrics), and built an internal deployment tracker integrated with CI/CD that replaced manual spreadsheet/Slack processes.”

“Backend engineer focused on cloud/distributed systems, deploying Java 17/Spring Boot microservices on AWS EKS with RDS and Kafka. Demonstrated strong production readiness work (DB lock mitigation, Kafka idempotency, gradual rollouts) and delivered a major latency improvement (~400ms to ~100ms). Also has proven cross-layer troubleshooting skills, isolating intermittent API timeouts to a specific Kubernetes node’s network interface issue, and partners closely with ops teams to build dashboards and workflow automation (including Python scripts).”

“ML/LLM practitioner with production experience building a healthcare review sentiment pipeline (RateMDs) using Hugging Face Transformers plus a LangChain+FAISS RAG layer for interactive querying. Also led orchestration-driven optimization of Nike’s Fusion ETL pipeline, improving runtime efficiency by 20%, and has experience translating ML outputs into Tableau dashboards for non-technical healthcare stakeholders (e.g., readmission risk).”

“Worked on payments and wallet transactions, with an emphasis on observability and root-cause analysis. Delivered end-to-end A/B testing optimization and implemented Jenkins-based CI/CD automation that reduced manual implementation to 35% and cut deployments to ~2 minutes, with attention to operational considerations like on-call/call rotations.”

“World of Warcraft quest designer who owned end-to-end quest pipelines and shipped standout content, including the memorable escort/stealth quest “Klaskin’s Great Escape” tuned through playtests and a Dragonflight capstone framing story that drove higher side-quest engagement. Experienced in Lua scripting, reward/economy balancing, and building daily/weekly endgame loops (Beetle Ranch/Rak-Ush), with recent UE5 Avalanche node-based VFX prototyping exposure.”

“Game QA Lead/embedded QA with live production experience supporting a public alpha, owning narrative/early-game content quality and quest progression stability. Known for driving rapid resolution of high-impact blockers via consistent repros, cross-discipline coordination, and data-backed reporting (including bot-based success/failure measurement), while maintaining sprint-aligned test plans and documentation in JIRA/Confluence and leading developer playtests for gameplay feel/polish.”

“Data engineer with Intuit experience owning end-to-end, high-volume financial data pipelines (API/S3 ingestion, Airflow orchestration, Spark/PySpark + SQL transforms, Snowflake marts). Strong focus on reliability and data quality—achieved 99.8% SLA and cut discrepancies by 35% using Great Expectations, reconciliation, schema versioning, and automated backfills; also built near real-time Kafka/API data services with CI/CD and observability.”