Senior Site Reliability Engineer - Site Reliability Engineering & AI Platform Operations

HelloPrint is mid-transformation. The entire platform is being rebuilt from the ground up: new frontend, new pricing engine, new content engine, new product engine. Everything agent-ready. We ship in a week what used to take a year. What we do not yet have is someone who owns the reliability of all of it: the SLOs, the cost, the AI runtime, and the guardrails that let product engineers move fast without breaking things. That is this role.

Core Objective: Take full technical ownership of production reliability, distributed observability, deployment safety, cost optimization, and AI runtime infrastructure across high-velocity microservices and cloud workloads.

What you will do:

• SLOs & Error Budgets: Define, track, and enforce Service Level Objectives (SLOs), Service Level Indicators (SLIs), and error-budget policies across core customer journeys and critical services (including checkout, payments, catalog pipelines, and routing engines).

• Distributed Observability & Telemetry: Expand Telemetry, Sentry + Google Cloud Monitoring distributed tracing, and automated diagnostic tooling across microservices, Laravel Horizon queue workers on Redis, and Google Cloud infrastructure.

• Deployment Safety & Progressive Delivery: Partner with product teams to evolve CI/CD pipelines with canary traffic shifting, automated SLO-driven rollbacks, and automated health gates in GitHub Actions.

• AI Platform Operations & FinOps: Architect, monitor, and scale the runtime infrastructure supporting AI agents, semantic pipelines, and background automation. Take full ownership of runtime cost control, model and token budget tracking, latency profiles, rate limits, queue backpressure, and provider availability.

• Cloud Infrastructure Cost & Budget Optimization: Partner with engineering leadership to drive continuous FinOps practices across Google Cloud workloads, actively identifying resource inefficiencies, optimizing compute/storage footprint, and enforcing infrastructure budget guardrails.

• Incident Management & Post-Mortems: Lead on-call incident response and blameless post-mortems, systematically turning root causes into automated tests, synthetic checks, and architectural guardrails.

• Resilience, Capacity & DR: Drive capacity forecasting, dependency isolation, automated load testing, and disaster recovery validations against strict RTO/RPO targets.

• Infrastructure as Code & Security: Own declarative infrastructure workflows using Terraform and Google Cloud Run, ensuring strict IAM least privilege, Secret Manager, and deterministic environments.

• Toil Elimination & DevEx: Build pragmatic internal tooling, runbooks, and self-service deployment primitives that eliminate firefighting and enable product engineers to ship reliably.

What we are looking for:

• Production SRE & Platform Background: Proven experience operating and scaling high-traffic distributed production systems where uptime, low latency, and safe release cycles are paramount.

• Deep Diagnostic Capabilities: Strong troubleshooting skills across Linux environments, containerized runtimes, relational/NoSQL databases, Redis queues, and cloud network boundaries.

• GCP & Serverless Container Stacks: Extensive hands-on experience with Google Cloud Platform, Google Cloud Run, and infrastructure automation via Terraform.

• Cost Governance & FinOps Mindset: Demonstrated ability to monitor, analyze, and optimize cloud and AI runtime costs, striking the right balance between performance, reliability, and budgetary efficiency.

• Targeted Monitoring & Tracing: Practical experience configuring Sentry (for error reporting and distributed tracing across Laravel and Astro frontends) alongside Google Cloud Monitoring for SLI tracking and canary gates.

• Automation & Scripting Skills: Proficiency in Python or TypeScript/JavaScript for platform tooling, combined with practical working familiarity with modern PHP in a Laravel ecosystem.

• AI Operations Affinity: Familiarity with operationalizing LLM integrations, embeddings/vector workflows, rate-limited external APIs, or background task orchestration.

• Engineering Mindset: Pragmatic builder with high technical agency who values durable system guardrails and deterministic automation over manual interventions.