Staff Software Engineer, Reliability

Staff Software Engineer, Reliability

Metropolis is an artificial intelligence company that uses computer vision technology to enable frictionless, checkout-free experiences in the real world. Today, we are reimagining parking to enable millions of consumers to just "drive in and drive out." We envision a future where people transact in the real world with a speed, ease and convenience that is unparalleled, even online. Tomorrow, we will power checkout-free experiences anywhere you go to make the everyday experiences of living, working and playing remarkable - giving us back our most valuable asset, time.

Who You Are

We are building a hyperscaler company and need someone to own reliability across the entire Metropolis platform. As a Staff or Senior Software Engineer focused on Reliability, you'll establish and drive the comprehensive reliability practices that ensure system availability, resilience, and observability for our mission-critical mobility infrastructure serving millions of transactions.

This is your opportunity to build reliability from first principles – architecting failover systems, implementing chaos engineering practices, and improving the observability foundation that will enable Metropolis to scale to new markets while maintaining 99.9%+ uptime. You'll be the technical owner of our reliability posture, working on everything from multi-region failover architectures to incident response workflows to SLO-based alerting strategies.

Our platform handles real-time payment processing, customer authentication, and parking facility operations – systems that cannot go down. You'll tackle challenges like external service failover, dependency mirroring to prevent upstream outages, database replication and automatic promotion, and building the monitoring and alerting infrastructure that ensures we detect and respond to issues in minutes, not hours.

If you're energized by the challenge of ensuring system reliability at scale, building robust failover mechanisms, implementing comprehensive observability, and establishing the practices that prevent incidents before they occur, this role is for you. You'll work alongside highly technical teams across the organization, influencing architecture decisions and establishing reliability standards that affect every service we build.

What You'll Do

Own the overall reliability posture for the Metropolis platform, establishing practices, metrics, and systems that ensure 99.9%+ uptime across all services

Design and implement automatic failover mechanisms for critical external dependencies (Twilio for SMS/voice, Stripe for payments) with circuit breakers, retry policies, and degraded mode operations

Architect and build active-passive or active-active regional deployment strategies with database replication, automated failover, and DNS-based traffic routing including disaster recovery planning and testing

Establish comprehensive monitoring using Datadog for APM, logs, and metrics correlation; implement synthetic monitoring, SLO-based alerting, on-call rotation, and escalation policies; build service health dashboards that show customer impact

Own the incident management process including workflows, tooling, post-mortem culture, runbook automation, and MTTR reduction initiatives – driving down mean time to recovery from detection to resolution

Drive adoption of resilience patterns across all services including health checks, graceful degradation, feature flags, rate limiting, backpressure mechanisms, and chaos engineering practices

Build and maintain local mirrors for critical dependencies (Maven/NPM/Docker registries) with artifact caching, dependency pinning, and vulnerability scanning to prevent build failures from upstream outages.

What We're Looking For

8+ years of backend software engineering experience with deep focus on distributed systems and platform infrastructure

Expert-level Java proficiency with deep understanding of JVM performance, concurrency, and ecosystem tooling. Scala experience is a big plus

Production experience with microservices architecture, container orchestration (Kubernetes), and cloud platforms (AWS)

Strong systems thinking with proven ability to design and implement large-scale, high-availability distributed systems that handle significant load

Observability expertise including hands-on production experience with metrics, logging, tracing, and alerting systems in high-load environments

Database and data systems knowledge including relational databases, event streaming (Kafka, SQS), caching strategies, and data consistency patterns

Experience with AI-powered development tools such as Claude Code, GitHub Copilot, or similar agentic coding tools for enhanced productivity – context engineering in particular

Excellent technical communication with ability to design and document complex systems, lead technical discussions, and collaborate across multiple teams local to New York City, Seattle, or Los Angeles area

While Not Required, These Are A Plus:

SRE or Reliability Engineering experience at companies known for operational excellence or high-growth startups where you built reliability practices from the ground up

Incident response leadership including experience building incident management processes, conducting blameless post-mortems, and driving MTTR reduction initiatives in production environments

Chaos engineering experience with tools like Chaos Monkey, Gremlin, or similar, including designing and executing game days and failure injection testing

Performance optimization experience with profiling, benchmarking, capacity planning, and system tuning at hyperscale including experience optimizing for high-throughput, low-latency systems

Open source contributions or technical blog writing that demonstrates depth of expertise in reliability engineering, distributed systems, or production operations

Our Stack

Languages + Frameworks: TypeScript, React, Scala (principally), Java (limited)

Datastores: MySQL, PostgreSQL, Snowflake

Cloud: AWS

Version control: Git & GitHub

AI Tooling: Copilot on GitHub

Observability: Datadog