Vetted Grafana Professionals

“Hands-on engineering manager at a marketing company leading a highly senior, distributed team (10 direct reports) while personally coding ~60–70% and owning end-to-end architecture across three interconnected products. Built agentic CRM automation and a reinforcement-learning-driven distribution layer for channel spend/bidding, with a strong focus on scalable design and observability (Prometheus/APM/logging) enabling frequent releases and few production incidents.”

“Software engineer with experience across Goldman Sachs, BYU Broadcasting, Juniper Networks, and an edtech startup (Doubtnut), spanning data migrations, AWS-based media backends, and microservices observability. Built a Redis/ElastiCache caching layer in front of DynamoDB/S3 to improve media delivery latency and cost, and created an SEO indexing automation tool using the Google Search Console API that saved ~15–30 person-hours per day.”

“Software engineer with ~2 years at UnitedHealth Group plus CMU coursework/TA experience, spanning backend modernization and cloud-native operations. Worked on migrating a customized open-source EDI system from Python 2 to Python 3 while improving SQLite database traceability via JSON exports, and has hands-on Kubernetes microservices deployment on Azure using Helm, HPA, and Jenkins-based Git-triggered CI/CD. Also built a large-scale real-time ride-hailing simulation using Kafka + Samza with explicit fault-tolerance strategies.”

“Backend/platform-focused engineer who builds scalable onboarding and data ingestion pipelines for complex client data formats, emphasizing staged validation, idempotent job boundaries, and safe rollouts behind feature flags. Strong in production diagnostics (Kibana/Logstash, SQL, debugger traces) with a concrete example of finding a regression causing incorrect Tax Loss Harvesting alert counts within a day, and experienced enabling both engineers and customer-facing teams through docs, runbooks, and technical walkthroughs.”

“Backend/data engineer focused on production ML/LLM systems: built a real-time FastAPI inference API on Kubernetes with strong reliability patterns (timeouts, idempotent retries, centralized error handling). Delivered AWS platforms using EKS + Lambda with GitHub Actions/Helm CI/CD and built Glue-based ETL from S3/Kafka into Snowflake with schema evolution and data-quality controls; also modernized legacy analytics/recommendation workflows into Python services with safe, feature-flagged cutovers.”

“Engineering leader (12+ years Director, 17 years lead) focused on developer productivity and platform/framework work across Oracle, PlayStation, Workday, and CafePress. Notable for building distributed teams from scratch and delivering high-impact platform architecture—e.g., re-architected PlayStation’s upload pipeline to support 500GB–5TB submissions using browser-to-AWS chunked uploads with SNS/SQS and deduplication/resume support.”

“AWS enterprise customer leader supporting the Apple Maps account, focused on large-scale migrations from on-prem (e.g., Cloudera) to AWS EMR/EBS. Known for deep troubleshooting and cross-functional execution (Grafana-driven autoscaling fixes, Graviton capacity/ICE mitigation) and for tying roadmap alignment to commercial outcomes, including a cited $30M incremental ARR expansion.”

“Backend/data-platform engineer with Stripe and Salesforce experience focused on global payouts/treasury systems. Built an end-to-end payout settlement monitoring platform (FastAPI microservices, Kafka/Spark streaming, React dashboard, CloudWatch alerting) that cut settlement delays 25% and reconciliation time 30%, and productionized an ML anomaly detection service that reduced missed issues by 30%. Experienced modernizing monoliths into microservices with feature flags/canaries and close partnership with treasury/risk/CTO stakeholders.”

“AI/LLM engineer who built and productionized an internal RAG-based knowledge system that ingests diverse sources (PDFs, Markdown, Slack), scaled retrieval with distributed FAISS and parallel ingestion, and reduced hallucinations via re-ranking, grounding prompts, and post-generation validation. Also has hands-on orchestration experience with Airflow and Kubernetes for reliable ETL/model pipelines, monitoring, and staged rollouts; reports ~15% accuracy improvement and adoption as the primary internal knowledge tool.”

“Built and operationalized an internal LLM/RAG system for engineering specs—starting with an at-home prototype using real ERP documents, then securing hardware, standing up a GPU/software stack, and deploying through UAT to production. Identified organizational gaps (no shared spec repository) and created a queryable RAG database that reportedly cut document discovery from days/weeks to minutes, while also resolving retrieval issues via improved PDF-aware chunking.”

“TikTok engineer (4 years) who built and owned multiple ad transparency platforms used by internal teams and advertisers worldwide. Strong full-stack profile spanning Next.js/TypeScript + Redux frontends, a secure/optimized BFF layer, and event-driven backend workflows (Kafka, retries/DLQ, Redis idempotency) with heavy emphasis on observability and performance; cites a 20% moderation efficiency gain on a modernized legacy tool.”

“Built and deployed a production LLM-powered RAG document intelligence system used by non-technical enterprise stakeholders, cutting document search time by 40%+ while improving answer consistency. Demonstrates strong MLOps/data workflow orchestration (Airflow, AWS Step Functions, managed schedulers across GCP/Azure) and a metrics-driven approach to reliability, evaluation, and cost/latency optimization with guardrails and observability.”

“ML/LLM engineer with Stripe and Adobe experience who productionized a transformer-based Payments Foundation Model for real-time fraud detection at global scale (billions of transactions). Built petabyte-scale ETL/feature pipelines (Spark/EMR, Airflow, dbt, Kafka/Flink) and achieved <100ms multi-region inference (EKS, TorchServe, edge/Lambda, GPU/CPU routing) with strong PCI-DSS/GDPR compliance and explainability (SHAP/LIME), reporting a 64% fraud accuracy improvement.”

“End-to-end product engineer who built and shipped Shopify Magic, an LLM-powered product-description generator on Amazon Bedrock with RAG over a tenant-isolated vector database, achieving 50% faster content creation, sub-2s latency, and 70%+ merchant adoption. Also led a Flexport migration from a monolithic Rails app to microservices using feature flags and parallel runs, delivering zero downtime and a 60% improvement in development speed.”

“LLM-focused engineer/sales-engineering profile with hands-on experience productionizing complex systems: scalable distributed architecture, multi-tenant monitoring, canary/shadow rollouts, and robust fallback strategies. Demonstrated real-time troubleshooting depth (p99 latency spikes traced to DB connection limits causing retry storms) and strong developer-facing communication via RAG workshops and live, customer-specific demos that helped close deals quickly.”

“ML/NLP engineer with experience building production-grade legal-tech and data platforms, including a GPT-4/LangChain contract review system using ElasticSearch embeddings (RAG) deployed on AWS EKS. Strong in entity resolution and scalable batch/streaming pipelines (Kafka/Spark), with measurable impact (70%+ reduction in contract review time) and a focus on monitoring and CI/CD for reliable delivery.”

“Engineering leader in cloud security at SysTech with player-coach experience spanning cross-team data/ownership standardization and reporting platform user-journey improvements. Stays technically deep through observability (SLA/SLOs, dashboards, alerting), rigorous code reviews (including AI-assisted coding), and end-to-end incident ownership in IAM/agentless cloud event collection. Targeting $270K–$300K base plus bonus/equity.”