Vetted Prometheus Professionals

“Has hands-on familiarity with successful F2P mobile fighting games (e.g., Marvel Contest of Champions) and can articulate key retention/monetization systems like streak-based daily logins, gacha rewards, and limited-time events. While not having shipped a game directly, they have shipped web/mobile products integrated into gaming ecosystems and think in terms of live-ops health metrics and A/B testing for IAP offers.”

Surya Teja

Screened

Mid-level Backend/Full-Stack Engineer specializing in AI and FinTech payments

Tempe, AZ4y exp

“Full-stack engineer who has owned an operational reporting/dashboard product end-to-end—building a React UI, designing/implementing FastAPI services, and deploying/operating on AWS. Demonstrates strong performance engineering (Postgres query/index tuning using EXPLAIN ANALYZE) with concrete impact (reports reduced from tens of seconds to a few seconds) and a reliability mindset across observability, migrations, and resilient third-party/ETL integrations.”

“Backend/data engineer with production experience building FastAPI services with strong reliability patterns (circuit breaker, rate limiting, caching, graceful degradation) and JWT/OAuth2 auth. Has delivered AWS EKS deployments via Terraform with Secrets Manager/IRSA and HPA autoscaling, and built Glue/Spark ETL pipelines on S3 Parquet with schema-evolution and idempotent reruns; also demonstrated measurable SQL tuning impact (20–30s to <10s).”

“Backend/data engineering candidate with Netflix experience designing and migrating analytics platforms from batch to real-time streaming (Kafka/Flink) across AWS and GCP. Delivered measurable improvements (40% lower data delay, 99.9% accuracy) using phased rollouts, automated data validation (Great Expectations), and strong observability (Prometheus/Grafana), and proactively hardened pipelines with idempotency to prevent duplicate Kafka processing.”

Likhitha Bethi

Screened

Mid-level Software Engineer specializing in backend systems, distributed systems, and applied AI

Stony Brook, NY4y exp

“Goldman Sachs engineer who owned end-to-end features for an internal onboarding and case management platform, spanning React/TypeScript UI, a GraphQL gateway, and Node + Spring WebFlux microservices. Built and operated a Kafka-based ingestion and search pipeline with DLQs, retries, idempotency, and strong observability, and improved developer experience via backward-compatible GraphQL API design and schema-driven documentation.”

“Internship experience at Intuit building an LLM-grounded QA system for internal microservice data across 100+ microservices, using a graph database approach (evaluated Neo4j and selected AWS Neptune for production alignment). Also has UC Berkeley research experience (including work with Prof. Dawn Song / Berkeley Eye Research Lab) and cross-functional collaboration with bioinformatics/biology teams to deploy software systems on research servers.”

“Gameplay engineer with hands-on ownership of a real-time C++ combat ability system, including diagnosing and eliminating large-scale combat frame spikes by refactoring hit detection to an event-driven, animation-notify approach (cut collision checks ~80%). Also implemented UE5 networked abilities (dash) with client-side prediction and server-authoritative reconciliation, plus projectile ballistics validated through debug spline visualizations and unit tests.”

“Infrastructure/platform engineer with hands-on experience running production and non-production Amazon EKS clusters, including upgrade processes and reliability monitoring via Prometheus/Grafana. Also administered on-prem VMware vSphere/vCloud Director and handled a significant vSwitch/VLAN outage, and uses Terraform + Terragrunt with S3 remote state and release-based drift detection across dev/stage/prod.”

Zheng Wu

Screened

Junior Software Engineer specializing in backend systems and cloud messaging

Mountain View, CA1y exp

“Data/ML engineer who has owned end-to-end systems across email deliverability/segmentation and production LLM apps. Built a Spark+Airflow segmentation engine that materially improved deliverability (99.9%) and open rates (>50%), and shipped a PDF-to-quiz RAG product using LangChain/Vertex AI/Chroma with strong guardrails and an eval loop that cut hallucinations to <5%.”

KARTHIKBABU VADLOORI

Screened

Mid-level Full-Stack Developer specializing in Spring Boot, React, and cloud microservices

San Francisco, CA5y exp

“Backend engineer with experience at Meta and Accenture building regulated-data systems (healthcare/financial) using Python/Flask and Postgres. Has scaled high-throughput services to millions of daily requests, delivering measurable latency wins (~40% API latency reduction; ~35% faster DB-backed endpoints), and has productionized ML inference services using Docker/Kubernetes and AWS (ECS/SageMaker).”

“AI/full-stack engineer with hands-on production experience across React/TypeScript, Go, and Python, spanning an early-stage education startup and a compliance-sensitive internal healthcare data platform. Stands out for shipping LLM and retrieval-based products with measurable impact, including a 27% recommendation improvement, support for 1M+ daily events, and a 19% lift in task completion in a secure, auditable environment.”

Kshitij Kakade

Screened

Intern-level AI/Full-Stack Engineer specializing in LLM systems and RAG

Mountain View, CA2y exp

“Product intern at KNEX who stepped into engineering ownership when the team was reassigned and shipped a lease abstraction AI agent that cut data-entry time by roughly 85% in a live CEO demo. Also built a full-stack agentic RAG app with React/TypeScript, FastAPI, pgvector, hybrid retrieval, tool use, and citation-based transparency, showing unusually strong end-to-end AI product depth for an early-career candidate.”

Shivam Gupta

Screened

Mid-level Software Engineer specializing in distributed systems, AI, and FinTech

USA5y exp

“Full-stack engineer with experience at AWS and Barclays, spanning large-scale cloud infrastructure, customer-facing product development, and production GenAI systems. Stands out for owning systems end-to-end—from backend architecture and frontend UX to AI reliability and cost optimization—with measurable impact including 25% fewer support tickets, 10% subscription growth, and debugging time reduced from 30 minutes to 5 minutes.”

“Internship experience deploying cloud-based services into production, including navigating security/resource provisioning and coordinating approvals across impacted teams. Built a Python backend for a local Ollama-based app using open-source models, and has hands-on distributed systems experience implementing and debugging Paxos with extensive logging/state tracing.”

“AppSec/customer security specialist with Atlassian enterprise cloud migration experience, advising on SSO and API token hardening and driving adoption through phased rollouts. Implemented Snyk (SCA) and SonarQube (SAST) in Bitbucket Pipelines with Jira-based vuln workflows, cutting critical vuln MTTR from 30 to 7 days for financial services customers. Strong in SSO troubleshooting (Okta/SAML) and secure AWS/EKS-based agent integrations with secrets management and Datadog observability.”

“Engineering lead/player-coach at Sam's Club who drove major React Native Member Desk Returns changes (including Vision Center insurance refund flows) by coordinating Product/UX, QA, and API teams and leading a 3-engineer squad. Also led an e-commerce mobile OAuth migration, evolving a login experience from vanilla JS to a React SPA as security requirements (MFA, reCAPTCHA) emerged, and improved production reliability via better request flagging and analytics/log instrumentation.”

Yashwanth J

Screened

Mid-level Software Engineer specializing in AI/ML and full-stack systems

Seattle, WA4y exp

“Engineer with Apple experience building LLM-powered internal workflow orchestration systems using Python, LangGraph, FastAPI, Redis, vector search, and Kubernetes. Stands out for a highly pragmatic, production-focused approach to agentic systems: deterministic state management, strong guardrails, observability, and human review for high-risk actions.”

“Senior frontend engineer focused on complex internal operations and payment products, with deep experience building React/TypeScript dashboards for payments, subscriptions, and observability workflows. Stands out for going beyond UI implementation to shape API contracts, real-time architectures, performance strategy, and product behavior across support, finance, and engineering use cases.”

“AI/LLM-focused engineer with hands-on experience building RAG pipelines, prompt engineering workflows, and multi-agent systems using tools like LangChain. Stands out for combining AI-assisted development with production-grade validation and for leading the architecture/orchestration of agent-based recommendation systems that improved response time, accuracy, and scalability.”

“Backend/data engineer with Optum healthcare claims domain experience building high-reliability Python microservices (FastAPI/Kafka/Postgres) and AWS data platforms (EKS, Glue, Redshift). Demonstrated strong production ownership: fixed duplicate Kafka processing via transactional outbox/idempotency, scaled to millions of daily events, and delivered major SQL performance gains (40+ min to <5 min, ~60% CPU reduction). Seeking remote-only work; targets $130k base.”

“Backend/data engineer with production experience at Walmart and HealthSnap building Python services and data pipelines on AWS (EKS, Lambda, Glue, Airflow). Strong reliability and operations focus—implemented idempotency + circuit breakers for peak-traffic consistency issues, GitOps CI/CD, and observability. Demonstrated measurable performance wins (Postgres p95 45s to <5s, ~60% CPU reduction) and modernized SAS batch workflows to Python with parallel-run parity validation and feature-flagged rollout.”

“Backend/data engineer who has owned production Python APIs and high-throughput async workflows on AWS (FastAPI, Docker, ECS/EKS/Lambda) with mature reliability practices like idempotency, bounded retries, circuit breakers, and strong observability. Also built AWS Glue ETL into an S3/Redshift lakehouse and modernized legacy batch systems via parallel-run parity testing and feature-flagged migrations, including a SQL tuning win cutting a multi-minute query to under 10 seconds.”

“Full-stack engineer (Snowflake) who shipped an AI/LLM-powered data exploration product end-to-end, spanning Spring Boot/Python services and a polished React UI with streaming responses and robust fallbacks. Experienced operating high-scale AWS deployments (Docker/Kubernetes, SNS/SQS, RDS Postgres, CloudWatch, Jenkins CI/CD) supporting thousands to tens of thousands of concurrent users, including handling real traffic-spike scaling incidents.”