Vetted Grafana Professionals

George Platon

Screened

Principal Full-Stack Engineer specializing in AI, DevOps, and cloud platforms

Romania, Romania16y exp

“Built a production end-to-end AI video-to-reels clip extraction system using a multi-agent architecture with transcription, captioning, effects generation, and centralized orchestration. Demonstrates unusually strong systems thinking around reliability, observability, evaluation, and production tradeoffs for LLM-powered workflows, including Kubernetes/Kafka-based deployment and regression-driven prompt governance.”

“Engineer with a mature, agent-oriented approach to AI-driven software development, using structured planning, TDD, and verification loops rather than ad hoc prompting. Has hands-on experience acting as a tech lead for multiple AI agents in an LLM intelligent routing project, coordinating implementation, testing, debugging, and edge-case review with strong attention to system tradeoffs.”

Lenny Lin

Screened

Junior Full-Stack Engineer specializing in AI and distributed systems

Champaign, IL3y exp

“Built and owned a hackathon project (Gritto) with a Python/FastAPI backend that routes user text through a sequence of Gemini agents to produce structured JSON outputs. Has hands-on production deployment experience using Docker/Docker Compose, GitHub Actions CI/CD, AWS App Runner, MongoDB, and secrets management (Doppler + migration to AWS Secrets Manager), plus implemented a chat-like experience via multiple HTTP requests when SSE wasn’t viable.”

“Software engineer using AI pragmatically to accelerate development while keeping human review central to quality. Has hands-on experience applying AI and lightweight multi-agent workflows in a microservices environment spanning Java Spring Boot APIs, React modules, and Kafka event flows, with strong emphasis on architecture validation and production safeguards.”

“Backend/data engineer who helped evolve Bitnimbus LLC’s Kafka-as-a-service MVP from a monolith into an event-driven distributed system, using careful design, parallel rollouts, and idempotent event handling to maintain correctness. Also built production-grade API and database security (JWT scopes, rate limiting, explicit Postgres policies/RLS-style controls) and improved Prometheus monitoring by eliminating false outages via heartbeat metrics and windowed aggregation.”

“LLM/agentic-systems practitioner who has repeatedly taken LLM-driven pricing/decision services from prototype to production using pilots, guardrails, observability, and staged rollouts. Demonstrates strong real-time incident troubleshooting (dependency timeouts, cached fallbacks) and post-incident hardening (isolation/async/alerts), and also supports go-to-market via developer workshops, technical demos, and sales-aligned POCs.”

“Backend/platform engineer with hands-on ownership of Kubernetes GitOps delivery (GitHub Actions + Argo CD) on AWS EKS, including progressive rollouts and reliable rollback across interdependent microservices. Built a Python/FastAPI ML-driven document-processing service (PostgreSQL + S3) to complement existing Spring Boot systems, and implemented Kafka streaming pipelines with Schema Registry plus Prometheus/Grafana observability. Also supported a hybrid cloud-to-on-prem migration for compliance/latency with phased rollout and incremental PostgreSQL migration.”

“Built and operated an end-to-end customer-facing "Record Platform" web product as both engineer and primary user, focusing on reliability and correctness in core flows like search and checkout. Implemented a TypeScript/React frontend with a multi-service backend and Kafka-based event-driven architecture, and created internal tooling to automate risky ops like Kubernetes TLS certificate rotation with k6 load/chaos testing (including HTTP/2 and HTTP/3 validation).”

“Built and deployed a production RAG-based enterprise document intelligence platform for financial/compliance/operational documents on AWS (Spark/Glue ingestion, embeddings + vector DB, LangChain orchestration, REST APIs on Docker/Kubernetes). Deep hands-on experience orchestrating multi-step and multi-agent LLM workflows (LangChain, LangGraph, CrewAI) with strong focus on grounding, evaluation, observability, and cost/latency optimization, and has partnered closely with non-technical finance/compliance teams to drive adoption.”

“Cloud/hybrid infrastructure engineer with McKesson experience migrating tightly coupled healthcare applications to microservices on AWS EKS. Strong in IaC-driven standardization, CI/CD automation, and production observability (CloudWatch/Splunk/Prometheus/tracing), with demonstrated ability to debug complex incidents spanning Kubernetes and cloud networking.”

“Backend/AI engineer with Johnson & Johnson experience building data-heavy payer/claims analytics services (Python/FastAPI, PostgreSQL, AWS) and optimizing them under peak ingestion load via indexing/query tuning and caching. Also shipped an end-to-end RAG feature for clinicians to extract insights from unstructured clinical notes, using constrained prompts and retrieval-confidence guardrails to prevent hallucinations.”

“Backend-focused engineer with experience owning a production e-commerce platform end-to-end (TypeScript/Node/Express, React, MongoDB, Redis) including RBAC and contract-based API development. Also worked at Infosys on a large healthcare management system built with Spring Boot microservices, using Kafka for messaging/retries, circuit breakers for resilience, and OpenTelemetry/Swagger for observability and API documentation.”

“Backend/data platform engineer who owned a FastAPI + Kafka microservice in Verizon’s billing pipeline, handling high-volume usage ingestion/validation/enrichment with strong observability and CI/CD on AWS EKS. Demonstrated measurable performance gains (latency down to ~120–150ms; Kafka throughput +30–40%; DB CPU -25%) and led an on-prem ETL-to-AWS migration using Terraform, parallel validation, and phased cutover with zero downtime.”

“ML/NLP engineer with hands-on experience building production systems for unstructured insurance claims and customer data linking. Delivered measurable impact at scale (millions of documents), combining transformer-based NLP, vector search (FAISS/Pinecone), and human-in-the-loop validation, and has strong production workflow/observability practices (Airflow, AWS Batch, Grafana/Prometheus).”

“Built and deployed a production Llama 3-based RAG document Q&A system using FAISS, addressing context-window limits through chunking and keeping retrieval accurate by regularly refreshing embeddings. Has hands-on orchestration experience with LangChain and LlamaIndex for multi-step LLM workflows (including memory management) and collaborates with non-technical teams (e.g., marketing) to deliver AI solutions like recommendation systems.”

“Infrastructure/DevOps engineer (Geico) focused on AWS and Kubernetes at production scale. Has hands-on experience building secure GitHub Actions CI/CD for EKS, provisioning core AWS infrastructure with Terraform/CDK, and leading end-to-end incident response with post-incident automation to prevent recurrence; no direct IBM Power/AIX/PowerHA experience.”

“Built and shipped AI-powered workflow automation at Oracle, including an MCP-based agentic workflow with tool-calling and guardrails, plus Grafana monitoring and Confluence documentation. Also led a Django monolith-to-microservices migration at Chamsmobile using blue-green deployment and load balancer traffic splitting to avoid regressions while modernizing production systems.”

Aakanksha Desai

Screened

Junior Full-Stack Software Engineer specializing in React, Kubernetes, and AI-powered apps

Scottsdale, Arizona2y exp

“Backend/DevOps-leaning engineer managing multiple customer service platforms end-to-end (requirements through deployment). Built an in-house Python monitoring/alerting solution for Salesforce-to-Java contact sync jobs (Snowflake dependencies) that increased uptime ~60%, and helped modernize delivery by moving the team from manual releases to automated Jenkins-based deployments while coordinating an Oracle EBS→Fusion transition with business/data/IT stakeholders.”

Manasa Pippera

Screened

Senior .NET Full-Stack Developer specializing in cloud, IoT messaging, and real-time web apps

Franklin, TN6y exp

“Full-stack engineer who owns customer-facing web products end-to-end (React/TypeScript + Node.js), shipping frequent releases with strong testing, staged deploys, and production monitoring. Improved a key user flow by batching backend calls and simplifying frontend rendering, driving ~30% faster load times and ~30% higher completion rates. Also built an ops monitoring dashboard using ELK + Prometheus/Grafana that cut incident response time by 40% and has hands-on microservices messaging experience (RabbitMQ/Kafka, idempotency, DLQs).”

Ramya Konda

Screened

Mid-level AI/ML Engineer specializing in healthcare ML and generative AI

Remote, USA5y exp

“AI/LLM engineer at Humana who built and deployed a HIPAA-aware RAG system for clinical record retrieval, cutting search time dramatically and improving retrieval efficiency by 30%. Experienced with Spark-scale data preprocessing, QLoRA fine-tuning, LangChain orchestration, and MLflow+SageMaker integration, with a strong testing/evaluation discipline (A/B tests, human eval) to hit 95%+ accuracy and production latency targets.”

Raj Patel

Screened

Junior Machine Learning Engineer specializing in LLMs and RAG systems

Remote, USA1y exp

“Production-focused applied ML/LLM engineer who has deployed an LLM-powered RAG assistant and improved reliability through rigorous retrieval evaluation (recall/MRR), reranking, and guardrails that prevent confident wrong answers. Experienced running containerized ML/LLM services on Kubernetes (including AWS-managed layers) with CI/CD and observability, and has delivered a real-time predictive maintenance system using streaming sensor data and time-series anomaly detection in close partnership with maintenance teams.”

Sumanth Gottipati

Screened

Mid-level Full-Stack Software Engineer specializing in cloud-native microservices and FinTech

New York, NY4y exp

“At Delta Airlines, built and shipped a production LLM-powered semantic search/troubleshooting assistant over maintenance logs and operational documentation using OpenAI embeddings and a vector database. Implemented hybrid ranking, query enrichment, and structured filters to improve relevance ~35% while optimizing latency via caching and vector tuning. Also designed a scalable Kafka + AWS (Lambda/SQS) ingestion pipeline with strong reliability/observability and an eval loop using real engineer queries and human review.”

Ramyasree K

Screened

Mid-level DevOps/Cloud Engineer specializing in AWS infrastructure automation

Boston, MA4y exp

“Frontend engineer with experience building a large-scale React + TypeScript administrative dashboard for an e-commerce platform, using Redux Toolkit plus TanStack Query to separate UI and server state. Emphasizes quality at scale through CI/CD automation, Jest/integration testing, and performance techniques like code splitting and caching, with experience coordinating integration across multiple teams.”

Ramya Sree Kanijam

Screened

Mid-level Software Engineer specializing in backend systems, cloud, and AI pipelines

Remote, USA3y exp

“Built and owned an end-to-end AI-driven content enrichment pipeline for a news workflow, using n8n, LLM agents, and external APIs to automate ingestion, deduplication, categorization, and approval routing. Stands out for production-minded AI systems work: they improved reliability with schema validation, retries, idempotency, and monitoring, while automating 90% of processing and cutting duplication errors by 95%+.”