Vetted Site Reliability Engineering Professionals

“Hands-on engineering manager/lead focused on Azure application deployments and CI/CD automation. Has led design sessions and 1:1 code reviews, and owned a production performance incident end-to-end from measurement and test-environment setup through production validation, while coaching team members via regular 1:1s.”

Tuukka Luolamo

Screened

Executive Technology Leader (CTO) specializing in AI, cloud, and distributed platforms

Remote14y exp

“Engineering leader who stays hands-on in high-leverage technical areas (architecture, scalability, reliability) while operating at an executive level. Led StagePilot’s shift from a tightly coupled legacy system to a cloud-native, event-driven real-time platform proven at 1M+ concurrent users, and previously scaled multiple SRE teams at McGraw-Hill with SLOs, on-call, and blameless ops practices.”

Jax Diagana

Screened

Senior AI Engineer specializing in forward-deployed voice agents and incident-response automation

San Francisco, CA7y exp

“FDE at Bland.ai and founder of Fi (incident-response agent) who routinely takes LLM/agentic concepts from prototype to production. Has hands-on experience reverse-engineering undocumented systems to deliver integrations, building LLM testbeds for voice-agent reliability, and rapidly shipping RAG/semantic search solutions (e.g., Confluence runbooks) after deep customer discovery with DevOps/SRE teams.”

Steve Van Treeck

Screened

Engineering executive specializing in SaaS platforms for transportation & logistics

Denver, CO18y exp

“Pragmatic, Lean Startup–oriented candidate who prefers validating ideas through barebones MVPs and direct customer feedback, especially when entering unfamiliar markets. Motivated to partner with visionary founders and scale accessible products by lowering barriers to entry, while maintaining financial sustainability.”

“Has worked across multiple startup stages from pre-funding through Series D and emphasizes rigorous idea validation through direct conversations with both end users and purchasing decision-makers. Interested in applying NLP to automate summarization/abstracting of highly technical articles, with a balanced view of entrepreneurship that prioritizes health and family.”

Waldorff Villacres

Screened

Healthcare technology executive and architect with 20+ years leading enterprise platforms and digital transformation.

Seattle, Washington, USA21y exp

“Healthcare-focused founder in the R&D stage building an EHR and clinical staffing startup centered on value-based care. They have already tested the concept with the market, are engaging Medicaid/Medicare leaders and industry conferences like ViVE and HIMSS, and are focused on early-signal detection to improve patient outcomes while lowering utilization costs.”

“Full-stack product engineer with hands-on experience building a React/serverless/SQL e-commerce platform for Haagen-Dazs and improving consumer UX in a location-based animal discovery app. Stands out for pairing strong technical fundamentals—component architecture, SQL performance tuning, reusable primitives—with measurable product outcomes like 40% more completed orders, 25% customer growth, 95% navigation accuracy, and 20% fewer device malfunctions.”

“Senior engineering executive with 8+ years leading large-scale SaaS modernization across AI, compliance, ecommerce, streaming, IoT, and travel. Has led a 150+ global engineering org, modernized seven cloud-native platforms for a $400M business, and consolidated travel systems processing $1B+ annually while staying hands-on in architecture, incident response, and AI integration.”

Yash Priyadarshi

Screened

Junior Software Engineer specializing in distributed systems and cloud infrastructure

Bengaluru, India2y exp

“Backend/distributed-systems engineer who built a Golang distributed key-value store on AWS using Multi-Paxos, WAL, and non-blocking gRPC replication (cutting write latency ~40%) and proactively addressed tricky failure modes like leader-election livelock. Also developed a Python/Kubernetes cost-optimization scaling engine deployed with Helm/Terraform, delivering ~$40K annual savings while sustaining 99.99% uptime, and drives contract-first API development (OpenAPI/Swagger) to speed frontend integration.”

“Financial-services software engineer with experience building both full-stack advisor tools and production AI features at Charles Schwab. They owned an automated portfolio rebalancing workflow and helped launch an LLM-powered reporting assistant that cut report-writing time by 70%, while maintaining compliance through strict tool use, evals, and mandatory human review.”

“Product leader with experience spanning industrial AI, enterprise analytics, and live production tools at ProcessMiner, ADP, and Peloton. They’ve shipped ML-driven products that generated measurable operational savings and business improvements, including over $1.5M in annual chemical savings for manufacturing customers, and they pair that with deep stakeholder management and people leadership experience.”

“Small-team builder of Promethium’s “Mantra” next-gen agentic text-to-SQL engine, using vector DB + LangGraph tooling and SQL validation/evaluation to improve query accuracy. Experienced in diagnosing production LLM workflow failures via LangSmith traces and in running hands-on developer workshops and pre-sales POCs with live debugging and real customer data.”

“Cloud/Kubernetes-focused production engineer with experience running 99.95% uptime platforms across AWS/Azure/GCP. Strong in incident response and performance troubleshooting (including a 30% MTTR reduction), and in building secure CI/CD and Terraform-based IaC for AKS/GKE microservices with robust change controls and rollback practices. Notably does not have direct IBM Power/AIX/VIOS/HMC or PowerHA/HACMP ownership.”

Chris Colinsky

Screened

Executive Technology Leader/CTO specializing in data platforms, AI agents, and e-commerce/payments

Los Angeles, CA23y exp

“Engineering leader with hands-on coding time who has driven major commerce and data-platform transformations: defined goop’s omnichannel strategy, unified payments to Square, and rebuilt real-time NetSuite inventory flows plus forecasting tools. Currently reorganized engineering into Product/Data/Support teams to hit aggressive seasonal roadmaps, and led a data-lake/medallion ELT refactor feeding embedded analytics (Tinybird) with improved reliability and cost efficiency; also accelerates onboarding via AI coding tools in a serverless, event-driven architecture.”

Daniel Jin

Screened

Intern Site Reliability Engineer specializing in Kubernetes, AWS, and observability

New York, NY1y exp

“Backend/data engineering candidate specializing in Python/Flask services and ML-enabled systems, deploying containerized workloads on AWS ECS/EKS with strong observability (Prometheus/Grafana) and PostgreSQL performance tuning. Built multi-tenant architectures with row- and schema-level isolation and optimized a Kubernetes-based Airflow + Spark nightly ETL pipeline for an e-commerce client, improving performance by 250%+ and reliably beating morning reporting deadlines; also contributed to Apache Airflow (SQLAlchemy/PostgreSQL area).”

Deeresh Gajjala

Screened

Senior Software Engineer specializing in Java/Spring Boot microservices and AWS payments systems

Dallas, TX6y exp

“Senior software engineer with Amazon experience who owned end-to-end improvements to a real-time payment authorization service, rebuilding it as a reactive Spring WebFlux microservice with saga orchestration and Kafka event streaming, deployed on AWS EKS with strong observability. Also built React+TypeScript and Node/Express full-stack workflow apps (onboarding, campaign management, admin review) and has experience shipping quickly in ambiguous startup environments while maintaining reliability and data correctness.”

“Full-stack engineer with deep experience building enterprise compliance and certification systems at Paycom, including complex approval workflows, live migrations, and large-scale assignment processing. Particularly strong at turning ambiguous business rules into reliable backend workflow logic and at designing trustworthy GraphQL/AI-assisted user experiences backed by real-time system data.”

“Engineering/technology leader who stays hands-on while driving executive-level roadmap execution, with deep experience modernizing cloud-based LIMS/LIS platforms and building AI-driven lab analytics. Led a monolith-to-microservices cloud migration with containerization and CI/CD, and delivered a reported 30% reduction in lab turnaround time while strengthening compliance.”

Murali Marupudi

Screened

Mid-level Backend Engineer specializing in Python microservices and scalable systems

Jersey City, NJ4y exp

“Full-stack engineer with hands-on experience shipping both secure platform features and production AI systems. They combine React/TypeScript, Flask/Node.js, and PostgreSQL fundamentals with practical LLM and NLP implementation, including retrieval, schema-validated outputs, monitoring, and human-in-the-loop safeguards. Notable impact includes cutting manual review by 40% and reducing post-update error rates by over 20%.”

“Backend engineer who designed and evolved an AWS-based event-processing system in Python/PostgreSQL, achieving a 60% p95 latency reduction while improving reliability during traffic spikes. Led a zero-downtime migration from a monolithic Django app to FastAPI microservices using feature flags, strong testing, and cross-team coordination, with production-grade observability (Prometheus/Grafana/CloudWatch) and security (JWT/OAuth2, RBAC, Postgres RLS).”

Weston Carpenter

Screened

Mid-level Backend Software Engineer specializing in distributed systems

San Francisco, CA6y exp

“Technical/presales engineer with experience at Grubhub and Appen, spanning LLM-adjacent data labeling workflows and production AI troubleshooting. Built an integrations platform at Grubhub and has hands-on experience diagnosing prompt-related AI failures via Splunk, adding JUnit tests and logging to prevent recurrence. Known for shipping customer-specific workflow adaptations (e.g., OCR annotation coordinate transformations for crop/rotation) while keeping timelines intact through iterative delivery and parallelization.”

“Platform/infrastructure engineer with hands-on ownership of Kubernetes, Terraform, VMware, and hybrid on-prem/AWS environments. Stands out for combining deep platform build/upgrade experience with strong incident response and reliability practices, including a Terraform redesign at H&R Block that reduced provisioning time by 40% and hybrid networking improvements that hardened Direct Connect failover.”

“Full-stack engineer focused on AI-powered enterprise document automation, especially transforming unstructured financial documents into structured outputs. Stands out for treating LLMs and agents as components within robust production systems, with emphasis on validation, security, observability, and scalable multi-agent architecture.”

“Software engineer with unusually mature AI-native development practices, using Claude/GPT/Copilot across requirements, implementation, testing, and documentation. At Anzenna, they effectively acted as a tech lead for a multi-agent setup spanning four repos, creating specialized agent workflows and maintaining top-level cross-repo documentation to coordinate complex work.”