Metropolis
Senior Staff Software Engineer, Recognition Platform
$231K–$268K
Seattle, Washington, United States +2 · Senior Staff · Full-time · Posted Aug 26, 2026
- Location
- Seattle, Washington, United States
Los Angeles, California, United States
New York, New York, United States - Experience
- 12+ years; no alternatives stated.
About the job
Own the technical architecture and evolution of Metropolis’s Recognition Platform, transforming physical-world sensor signals into real-time actions through edge-to-cloud pipelines and decisioning systems.
What you'll do
- Lead platform architecture, RFCs, and roadmap sequencing across ingestion, identity resolution, decisioning, notifications, and operator surfaces.
- Build scalable streaming pipelines and real-time rules while aligning engineering teams and external partners.
- Own privacy, production quality, testing, rollouts, and technical standards; mentor engineers and promote AI-native workflows.
What they ask for
- 12+ years building and operating distributed, data-intensive production systems, including deep experience as a multi-service platform technical owner.
- Track record of cross-functional technical leadership and shared-architecture alignment.
- Expert proficiency in a JVM language such as Java or Scala, with fluency in event-driven and service-oriented design using gRPC/protobuf, streaming, and relational data modeling.
- Hands-on high-throughput ingestion pipeline experience and experience with rules, eligibility, or decisioning systems combining deterministic logic with probabilistic or model-driven signals.
Nice to have
- Experience with computer vision, biometric matching, sensor fusion, privacy-regulated domains, or consent management.
- Experience with IoT, edge computing, identity resolution, customer data platforms, or hospitality, retail, or physical-operations software.
Pay
$231,000 - $267,500 USD annually (base salary)
Tools
Scala, Java, gRPC/protobuf, TypeScript, React, MySQL, PostgreSQL, AWS
AI focus
Build decisioning systems that balance deterministic rules with probabilistic or model-driven signals, support model testing, and use AI-assisted engineering tools such as Claude Code and GitHub Copilot.
Model-written summary · the original posting is authoritative