Vetted Grafana Professionals

“Startup-style full-stack/backend engineer with hands-on AWS architecture experience who shipped an LLM-driven assessment-question automation feature (Python microservice calling AWS Bedrock via SQS, deployed on Lambda) with strong validation/guardrails and retry strategies. Also improved production scalability by moving a CPU/IO-heavy file upload path out of a Go API into a queue/Lambda design monitored with CloudWatch, and has React+TypeScript experience optimizing analytics dashboards.”

Homak Patel

Screened

Junior Software Engineer specializing in Agentic AI and Data Systems

2y exp

“Forward Deployed Engineer at EasyBee AI who productionized a self-storage customer’s multi-agent LLM system end-to-end—rebuilding it with LangGraph/CrewAI, integrating with real property management + CRM systems via an MCP server, and adding observability/guardrails for reliable daily use. Experienced in live troubleshooting of agentic workflows, developer demos/workshops (including an open-source project, MerryQuery), and partnering with sales to close deals through customer-specific technical demos and fast integration feedback loops.”

Manas Agarwal

Screened

Junior Full-Stack Software Engineer specializing in Python APIs, React, and cloud AI integrations

Superior, CO2y exp

“Customer-facing software engineer who builds and deploys practical AI/RAG solutions (e.g., an AI assistant for searching billing PDFs) by deeply understanding support workflows and iterating with users. Demonstrates strong production instincts—quickly stabilizing peak-traffic API timeouts with caching/background jobs, then implementing durable fixes with proper monitoring and maintainable code practices.”

Sanskar Pandey

Screened

Junior Full-Stack Java Developer specializing in FinTech microservices

OH, USA3y exp

“Full-stack engineer with production experience building a real-time order tracking system using React + Firebase/Firestore, emphasizing audit-friendly data modeling, state-machine-based status transitions, and strong post-launch ownership (performance, security rules, reliability). Demonstrated measurable frontend performance gains by isolating real-time updates to dynamic components and applying memoization, plus backend reliability patterns (idempotency, retries) and SQL query/index optimization validated with EXPLAIN ANALYZE.”

“Built and deployed real-world systems end-to-end across security and healthcare contexts: led a 3-person team delivering a university vehicle tracking system with 30% cost savings and 1-year post-launch monitoring. Also implemented a healthcare RAG chatbot with adaptive query routing that cut LLM costs by 40% while maintaining answer accuracy, and has experience debugging non-deterministic LLM behavior in DevOps pipeline automation.”

“Built and owned a production-grade RAG/LLM support automation system on AWS using GPT-4, Pinecone, FastAPI, and Redis, taking it from initial experimentation through deployment, monitoring, and iterative improvement. Their work reduced support workload and ticket volume by about 40%, improved CSAT and self-service resolution, and they also created shared Python/LLM infrastructure that accelerated other teams' delivery from weeks to days.”

“Candidate is actively using AI-assisted development tools, including MCP server integrations with Copilot, to generate boilerplate test scripts, validate code standards, and handle package updates. They also have hands-on experience choosing different agents based on task requirements and serving as an admin for AI tool access.”

“Software engineer with a strong builder mindset who has worked across ML, backend, and frontend systems. Notably built an AI-driven predictive autoscaler for Kubernetes from scratch using Prometheus, TensorFlow, Flask, and Spring Boot, and also delivered customer-facing automation features in financial document processing by working directly with auditors to translate domain rules into product logic.”

“Full-stack engineer who has shipped and operated generative-AI chat/QA features end-to-end, including a RAG-based pipeline with guardrails and cost/latency monitoring in production. Experienced with React/TypeScript + Node/Postgres architectures, Dockerized deployments to AWS (EC2) via GitHub Actions CI/CD, and building reliable ingestion/ETL systems with idempotency, backfills, and reconciliation.”

“Software engineer who builds workflow-centric products end-to-end, including a customer-facing module on the Trident AI content platform and an internal content workflow tool adopted as the default process. Strong in TypeScript/React + FastAPI architectures and in scaling event-driven microservices with RabbitMQ, emphasizing reliability (idempotency, DLQs) and observability (correlation IDs) to reduce outages and debugging time.”

“Cloud/DevOps-focused engineer with hands-on experience building Azure DevOps CI/CD pipelines for containerized applications deployed to AKS, including security scanning, approvals, versioned artifacts, and rollback. Also implemented Terraform-based IaC for Azure (VNets/subnets/NSGs/AKS) with modular design, remote state/locking, and drift detection; resolved a real deployment outage caused by an Azure RBAC permission change.”

Karan Baid

Screened

Intern Machine Learning Engineer specializing in Generative AI and RAG systems

Jaipur, India

“Early-career AI/LLM builder who created and deployed a multi-agent news analysis agent (Patrakarita) using CrewAI, coordinating researcher/analyst roles to turn noisy article URLs into structured, prioritized outputs (claims, tone, verification questions, opposing views). Strong focus on orchestration debugging and reliability evaluation, including measuring hallucination/redundancy and improving reasoning by refactoring pipeline sequencing.”

Srikar Tharala

Screened

Mid-level AI/ML Engineer specializing in Generative AI and RAG systems

Remote, USA4y exp

“Currently at ProShare and reports building an AI/LLM-powered system deployed to production, aimed at helping with status-related difficulties and reducing misunderstandings across transactions. Also cites prior collaboration at Porsche with marketing teams, focusing on translating marketing goals into technical requirements and communicating solutions clearly to non-technical stakeholders.”

“Product-minded full-stack engineer with experience in fintech identity verification and industrial analytics, focused on turning repeated operational pain points into reusable platforms. Built real-time KYC/KYB dashboards, secure cross-platform web components, and a multi-tenant workflow engine that cut onboarding from 2 weeks to 1 day while materially improving conversion, reliability, and developer speed.”

“Software engineer with hands-on experience spanning backend APIs, streaming data systems, and cloud/infrastructure automation, who is already using agentic AI workflows in a disciplined way. Stands out for combining practical systems work in Spring Boot, Kafka/Spark/ClickHouse, and Terraform/Kubernetes with a thoughtful approach to AI oversight, architecture, and multi-agent orchestration.”

“Senior full-stack developer who has operated in lean, multi-product engineering environments with significant end-to-end ownership. Strongest in JavaScript/TypeScript, React, and Next.js, with hands-on experience building a custom media player and internal business operations platforms that improved efficiency through dashboards, RBAC, search, and performance optimization.”

“Full-stack/backend-heavy engineer with strong healthcare domain expertise, focused on modernizing regulated platforms for payroll, billing, and caregiver operations. Notably led a legacy Express.js billing platform migration to modular NestJS services that enabled same-day deployments and unblocked enterprise customer onboarding, while bringing deep experience in compliance, auditability, and production reliability.”

“Frontend-focused engineer with experience in healthcare and fintech dashboards, especially around real-time data delivery and performance. In a growth-stage startup environment, improved dashboard architecture by replacing polling with React Query and GraphQL, leading to more responsive and reliable user experiences and fewer stale-data complaints.”

Ned Ned Zaidi

Screened

Senior Full-Stack Engineer specializing in Python, Go, and cloud-native systems

Dumfries, VA9y exp

“Full-stack/backend-leaning engineer with hands-on experience spanning Python, Go, React, Kafka, PostgreSQL, Redis, Docker, and Kubernetes. They stand out for building real-time analytics and decisioning systems, plus a healthcare-focused B2B SaaS compliance/data integration platform that combined high-throughput event processing, dashboarding, and third-party integrations in a startup-style, high-ambiguity environment.”

“Backend-focused engineer with deep healthcare interoperability experience, building Go-based distributed systems for live clinical data exchange across hospital systems. Stands out for combining startup-style ownership with HIPAA/compliance rigor, including creating a reusable Go microservice template and improving reliability across Kafka, PostgreSQL, and Kubernetes-based production platforms.”

“Frontend engineer with hands-on experience building production React/TypeScript dashboards for operations teams, including real-time ETL and service monitoring. Stands out for combining maintainable component design with practical performance optimization and map-based visualization work in data-heavy applications.”

“Senior backend/data engineer who has built and maintained HIPAA-compliant, real-time clinical FastAPI services on AWS, orchestrating ML/LLM and vector DB calls with strong reliability patterns (auth, timeouts/retries, graceful degradation, idempotency). Also delivered AWS IaC/CI-CD (Terraform/Helm/GitHub Actions) across EKS/Lambda/SageMaker and built Glue/Spark ETL with schema evolution and data quality controls, plus demonstrated large SQL performance wins (15 min to <9 sec) and hands-on incident ownership.”

“Backend Python engineer who owned the full backend build of an AI-driven platform for UK golf clubs, including FastAPI microservices, vector search, and a tuned LangChain+Pinecone RAG pipeline focused on cost and hallucination reduction. Experienced deploying Django/FastAPI/Flask stacks on AWS-backed Kubernetes with GitOps/ArgoCD-style delivery, plus executing legacy-to-AWS migrations and building Kafka-based real-time analytics pipelines.”

“Full-stack engineer with strong production experience improving performance and reliability of data-heavy analytics products. Has shipped end-to-end features spanning Node/Express + PostgreSQL + Redis and React/TypeScript, deployed via Docker/GitHub Actions to AWS EKS with Helm, and monitored with Datadog/CloudWatch; also built a Python compliance automation backend for AWS security monitoring with RBAC, versioned REST APIs, and resilient throttling-aware processing.”