Product & Engineering
Our platform optimizes billions in cloud spend across all major clouds, increasingly powered by ML models and LLM-driven intelligence. The stack is primarily Go and TypeScript, running on serverless infrastructure, with Python for our growing ML and data science workloads. Teams own their services end-to-end — you design, ship, monitor, and operate what you build.
Product teams span PerfectScale (AI-powered Kubernetes optimization), SELECT (ML-driven Snowflake, Databricks and BigQuery optimization), CloudWize (cloud security posture with anomaly detection), and LiveDiagrams (real-time infrastructure visualization). We're embedding LLMs deeply into the product — from natural-language cloud queries to AI-generated cost recommendations.
Every engineer gets unlimited Cursor, Claude Code, and Codex licenses. AI isn't a side project here — it's how we build. If you want to work on hard distributed systems and applied ML problems at real scale, with the autonomy to make architectural decisions that matter, this is the team.
Our platform optimizes billions in cloud spend across all major clouds, increasingly powered by ML models and LLM-driven intelligence. The stack is primarily Go and TypeScript, running on serverless infrastructure, with Python for our growing ML and data science workloads. Teams own their services end-to-end — you design, ship, monitor, and operate what you build.
Product teams span PerfectScale (AI-powered Kubernetes optimization), SELECT (ML-driven Snowflake, Databricks and BigQuery optimization), CloudWize (cloud security posture with anomaly detection), and LiveDiagrams (real-time infrastructure visualization). We're embedding LLMs deeply into the product — from natural-language cloud queries to AI-generated cost recommendations.
Every engineer gets unlimited Cursor, Claude Code, and Codex licenses. AI isn't a side project here — it's how we build. If you want to work on hard distributed systems and applied ML problems at real scale, with the autonomy to make architectural decisions that matter, this is the team.
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How We Build
The stack, the AI, and the principles behind the platform.
Languages
Core platform services, high-throughput data pipelines
Full-stack product surfaces, SDK clients, React front-ends
ML pipelines, LLM integrations, data science, and model serving
Infrastructure
Primary cloud — Cloud Run, BigQuery, Pub/Sub, GKE
PerfectScale runs on and optimizes K8s clusters at scale
IaC for all environments, PR-driven infra changes
Data & Storage
Analytics backbone for cloud spend intelligence
Real-time document store for product data
Caching, rate limiting, ephemeral state
AI & ML
GPT-4, Claude, Gemini — powering agentic systems for autonomous cloud management
Multi-agent orchestration, tool-use chains, and reasoning engines in production
Vector search pipelines for context-aware infrastructure recommendations
Developer Experience
Unlimited AI coding licenses for every engineer — no approvals
Monorepo, CI/CD via GitHub Actions, AI-assisted code review
Observability, APM, custom dashboards, ML-powered alerts
Deployment & Operations
GitOps-driven continuous delivery to production clusters
Serverless containers — zero-to-production in minutes
Progressive rollouts, A/B experiments, instant kill switches
Engineering Principles
Own it end-to-end
You design, build, deploy, and monitor your services. No hand-offs to a separate ops team.
Ship small, ship often
Trunk-based development, feature flags, and continuous deployment. Most PRs hit production the same day.
Make it observable
If it's not measured, it doesn't exist. Every service ships with metrics, traces, and structured logs from day one.
Design for scale
Our platform processes billions in cloud spend data. Systems are built to handle 10x current load without re-architecture.
Write it down
RFCs for major decisions, ADRs for trade-offs, runbooks for operations. The best code is the code that comes with context.
Automate the toil
If you're doing it twice, automate it. CI/CD, infrastructure, testing, deployments — we invest in developer productivity.
AI-native engineering
LLMs in the product, ML in the platform, and AI coding tools on every desk. We build with AI and we build AI.