Vetted Grafana Professionals

“Google Health engineer who owned and shipped an AI-powered clinical insights dashboard and NLP clinical note extraction service end-to-end (React/Next.js frontend; Python/Node microservices on GKE; TensorFlow transformers; BigQuery analytics). Demonstrated strong production rigor (CI/CD, testing, observability, guardrails for sensitive data) and delivered measurable outcomes including 30% faster diagnostics, 40% less manual documentation, 15% higher adoption, and 25% lower ops costs.”

Nicholas Ogura

Screened ReferencesStrong rec.

Executive Platform & Security Engineering leader specializing in multi-cloud Kubernetes and FinTech

San Diego County, USA18y exp

“Startup-focused infrastructure/security leader who stepped into head of engineering and re-platformed an entire product end-to-end in 3 months to meet launch. In crypto/fintech, recognized the market-data system as an ETL/data product and rebuilt it as a separable, securely accessible platform—prompting inbound interest within a week—while advocating an open-source-first observability stack (Prometheus/Grafana/Loki) to avoid vendor lock-in.”

Kyle Warneck

Screened

Director-level Frontend Engineer specializing in high-scale web platforms

Alameda, CA13y exp

“Former Epic Games engineering leader who built the web foundation of the Fortnite creator ecosystem, joining as the first web developer and scaling the team to 21 engineers as the platform grew to tens of thousands of creators and tens of millions of players. Combines deep frontend architecture expertise with backend/infrastructure ownership, observability, and product leadership across publishing, trust and safety, economy, analytics, and public APIs.”

“ML/LLM engineer who built and shipped an LLM-powered internal knowledge assistant at Meta, focusing on production-grade RAG to reduce hallucinations and improve trust. Deep experience with scaling and serving (FSDP/DeepSpeed/LoRA, Triton, Kubernetes autoscaling) and reliability practices (Airflow retraining, MLflow versioning, monitoring with rollback), including sub-100ms latency and ~35% GPU memory reduction.”

“ML/NLP engineer with experience at NVIDIA and Cruise building production-grade AI systems across genomics/biomedical research and autonomous vehicle data. Has delivered multimodal LLM pipelines, large-scale entity resolution, and hybrid semantic search (BERT embeddings + FAISS + Elasticsearch), with measurable impact (≈40% accuracy/retrieval gains; ≈30% data consistency improvement) and strong MLOps practices (Kubernetes, CI/CD, MLflow, Prometheus/Grafana).”

“Frontend engineer focused on sophisticated, high-performance browser UIs for internal operations teams. They have owned real-time monitoring and transaction-tracking interfaces, combining deep browser performance knowledge with user-centered workflow design to deliver sub-second responsiveness, 60 FPS rendering, and a 30% improvement in task completion speed.”

“Backend/data engineer with production experience at Uber building a near real-time driver rewards service on AWS (FastAPI, PostgreSQL, Redis) with strong reliability and concurrency controls. Also delivered AWS Lambda/ECS containerized deployments with GitHub Actions CI/CD and cost governance, built AWS Glue ETL with schema-evolution handling, and drove a ~10x SQL performance improvement while owning incident response via CloudWatch.”

“NVIDIA engineer who built and shipped a production LLM-powered enterprise knowledge system (summarization, transcription, and Q&A) that cut document retrieval time ~30%. Deep hands-on experience with RAG (FAISS/Pinecone), GPU-accelerated microservices on AWS, and reliability/safety practices (Guardrails AI, prompt A/B testing, canary releases) plus strong MLOps orchestration across Airflow, Step Functions, and Kubernetes GitOps.”

Chang Qian

Screened

Senior Backend/Infrastructure Engineer specializing in large-scale integrity and content systems

Menlo Park, CA10y exp

“Backend/platform engineer who built Bilibili’s "Avalon" content moderation platform from a vague CEO mandate into a company-wide service (Go, gRPC, Kafka), including on-call, metrics, transparency tools, and multi-site resiliency work. More recently at Meta, scaled a high-traffic mistake-prevention platform by introducing capacity levers (prefiltering, caching, log sampling, fanout limits) and navigating org-wide constraints, including debugging a rule-engine threading bottleneck.”

David Lapsley

Screened

Executive Engineering Leader specializing in AI infrastructure and cloud platforms

Tampa, FL14y exp

“Founder building Shipkode.ai, an enterprise SaaS product using generative AI to automate the front half of the software development lifecycle—from idea and customer feedback to engineering-ready specifications—with a beta planned for the first week of April. Has spoken with 24+ VCs over two years and mentors cybersecurity startups through the Tampa Bay Wave accelerator, emphasizing rigorous customer discovery to avoid misaligned product development.”

“Backend/full-stack engineer with experience building large-scale systems on Salesforce and eBay, including a sharded Oracle-backed personalization store used by millions of sellers and a Spring Boot microservice that executes scheduled payouts at high volume. Emphasizes production readiness via state-machine-based idempotency, strong observability (Splunk/Elasticsearch/PagerDuty), and extensive Selenium/Sauce Labs automation.”

“Backend/AI engineer currently at Stripe building Minions, an internal LLM-based developer agent that automates code generation, bug fixes, and PR creation. They combine strong production LLM architecture skills with reliability engineering, having improved routine PR merge times by ~40-45%, lowered post-merge bug rates by 12%, and previously built an invoice-processing pipeline that achieved 91% straight-through processing in a B2B payments context.”