Posted 4 weeks ago

Senior Staff Distributed Systems Engineer

IonQ

Santa Clara, CA, United States 🇺🇸

Onsite
Full Time
AWS
Azure
Google Cloud
Kafka

$216,136 - $282,978 year

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We are looking for a deeply hands-on Senior Staff Distributed Systems Engineer to join the team building IonQ’s Network and Security Platform
You will own the backend services — ingestion pipelines, telemetry processing, device management — that give operators real-time visibility into their networks and the intelligence to make them quantum-safe
This is infrastructure that matters: the systems you build will underpin IonQ’s mission to secure the world’s networks against quantum threats
In this role, you will own backend services end-to-end — from high-throughput ingestion pipelines collecting telemetry from large device fleets, to time-series storage, real-time processing engines, and the APIs that surface platform data to the rest of the organization
You are a deeply hands-on engineer who writes production-quality Go and/or Rust daily, takes pride in operational ownership, and brings strong distributed systems fundamentals to every problem you tackle
You will partner with and at times drive platform architecture decisions alongside the Principal Architect, setting technical direction for the platform and influencing how IonQ’s engineering org approaches distributed systems problems more broadly
Backend Services & Production Code:
Design and ship production backend services in Go and/or Rust, measured by code quality, test coverage, and on-time delivery of service milestones
Build and maintain high-throughput telemetry ingestion pipelines using gNMI, NETCONF, and SNMP, ensuring reliable data collection across large device fleets
Develop RESTful and gRPC APIs that expose platform data to internal consumers and external integrations, evaluated by uptime, latency SLAs, and adoption by downstream teams
Data Engineering & Storage:
Implement and evolve the time-series storage layer (InfluxDB, TimescaleDB, or equivalent), optimizing for query performance, retention policies, and data fidelity under production load
Build event streaming pipelines using Kafka or Kinesis with at-least-once or exactly-once semantics, validated through integration tests and production monitoring
Design data partitioning and archival strategies that sustain target ingest volumes while meeting defined latency and durability SLAs
Platform Reliability & Operations:
Own service reliability end-to-end — participate in on-call rotation, lead incident response, and drive systemic improvements tracked via post-mortems and reduction in repeat incidents
Instrument all services with structured logging, distributed tracing, and metrics (OpenTelemetry, Prometheus) so that production issues can be diagnosed and resolved within defined SLOs
Identify systemic reliability, scalability, or architectural gaps across the platform — not just within your service area — and drive org-wide initiatives to resolve them
Cloud-Native Infrastructure:
Package and deploy services as containerized workloads on Kubernetes, maintaining infrastructure-as-code (Terraform) across AWS, GCP, and Azure environments
Contribute to multi-cloud deployment patterns that meet platform availability targets and data residency requirements
Collaboration & Engineering Quality:
Partner with the Principal Architect to translate platform architecture decisions into tested, production-grade implementations with clear engineering specifications
Define the engineering standards, code review culture, and mentorship frameworks for the platform team; coach Staff and Senior engineers; and act as a cross-organizational technical resource for distributed systems and data infrastructure questions across IonQ
The ideal candidate has direct experience building data-intensive backend systems at scale — and is energized by the challenge of making complex infrastructure simple, observable, and dependable
12+ years of backend software engineering experience, with a strong record of shipping production services at scale
Established record of setting technical direction at the organizational level — shaping how engineering teams across IonQ approach distributed systems and infrastructure problems, beyond a single team or domain
Experience with cloud-native deployment: containerization (Docker), Kubernetes orchestration, and operating services across at least one major cloud provider (AWS, GCP, or Azure)
Strong fundamentals in distributed systems: consistency models, failure modes, backpressure, idempotency, and exactly-once vs. at-least-once processing tradeoffs
Solid experience building and operating distributed data systems: event streaming (Kafka, Kinesis, or equivalent), time-series databases, and high-throughput ingestion pipelines
Familiarity with observability tooling — structured logging, metrics (Prometheus/Grafana or equivalent), and distributed tracing (OpenTelemetry or equivalent)
Comfortable writing SQL and working with both relational and time-series data models; experience with schema design and query optimization
Strong engineering practices including TDD, code review, CI/CD, and on-call ownership — plus a demonstrated track record of defining and evangelizing these practices at the organizational level across multiple teams or companies
Proven, hands-on proficiency in Go and/or Rust — you write these languages regularly and can demonstrate production systems you have built with them
Experience with network telemetry protocols (gNMI, NETCONF, SNMP) or prior work at a network equipment vendor or network management platform company (e.g., Juniper, Cisco, Nokia)
Hands-on experience with graph databases or graph data models for network topology (e.g., Neo4j, Amazon Neptune, or custom adjacency representations)
Familiarity with YANG data modeling or prior experience working with device configuration schemas in network management contexts
Experience building multi-tenant SaaS backend services with strong data isolation and per-tenant resource management
Contributions to open-source infrastructure, observability, or networking projects; or published technical writing on distributed systems topics
Experience working in or adjacent to regulated, security-conscious environments (FedRAMP, NIST, or equivalent)

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