Principal Distributed Systems Engineer

IonQ•Santa Clara, CA

4d•Onsite

About The Position

We are looking for a Principal Distributed Systems Engineer to join the team building IonQ's Network and Security Platform. As a Principal Distributed Systems Engineer, you'll be part of a cross-functional team whose mission is to lead IonQ on its journey to build the world's best quantum computers to solve the world's most complex problems — and to secure the world's networks against quantum threats. In this role, you will be responsible for setting the technical direction and end-to-end architecture of the platform's distributed backend — the ingestion pipelines, event streaming and telemetry processing, time-series and data storage layers, and APIs that give operators real-time visibility into their networks and the intelligence to make them quantum-safe. You will remain hands-on: building reference implementations and proofs of concept, reviewing critical designs and code, and turning architecture decisions into production-grade systems alongside Staff and Senior engineers. The ideal candidate is a hands-on architect and natural technical leader who has designed and scaled multi-tenant, data-intensive distributed platforms, can align technology choices with business outcomes, and is energized by making complex infrastructure simple, observable, secure, and dependable.

Requirements

15+ years of software engineering experience building and operating distributed backend systems and platforms at scale, or an equivalent combination of education and experience.
Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
Demonstrated record as a hands-on architect: defining the architecture and multi-year roadmap for large-scale distributed platforms and driving them through to production.
Deep experience designing distributed data systems: event streaming (Kafka, Kinesis, or equivalent), high-throughput ingestion pipelines, and time-series or large-scale data stores.
Strong fundamentals in distributed systems: consistency models, failure modes, backpressure, idempotency, and exactly-once vs. at-least-once processing tradeoffs.
Hands-on proficiency in at least one production systems language (Go, Rust, Java, or Scala), with the ability to build reference implementations and review production code.
Extensive experience with cloud-native architecture on AWS (GCP or Azure a plus): containerization, Kubernetes, infrastructure-as-code, security, and cost optimization.
Experience designing multi-tenant platforms with strong data isolation, access control, and governance.
Experience defining observability and reliability frameworks — logging, metrics, tracing, SLOs — for mission-critical systems.
Established record of setting technical direction beyond a single team: leading architecture governance, influencing executive stakeholders, and mentoring senior engineers across globally distributed organizations.
Excellent written and verbal communication, with the ability to explain complex architecture tradeoffs to both engineering and business audiences.

Nice To Haves

Master's degree in Computer Science, Engineering, or a related discipline.
Production experience in Go and/or Rust.
Experience with network telemetry and network management platforms — gNMI/gRPC, NETCONF, SNMP, YANG data models — or prior work at a network equipment vendor or network management company (e.g., Juniper, Cisco, Arista, Nokia).
Experience with graph databases or graph data models for network topology (e.g., Neo4j, Amazon Neptune, or custom adjacency representations).
Experience with AI/ML platform infrastructure (MLOps / LLMOps, model governance, agentic workflows) applied to operational or network data.
Experience in regulated, security-conscious environments (FedRAMP, NIST, or equivalent).
Contributions to open-source infrastructure, streaming, observability, or networking projects, or published technical writing on distributed systems.

Responsibilities

Define and own the multi-year architecture and technical roadmap for the platform's distributed backend, measured by delivery against roadmap milestones and platform availability, scalability, and cost targets.
Lead architecture reviews and author the design standards, reference architectures, and decision records that guide how the platform — and IonQ's broader engineering organization — approaches distributed systems and data infrastructure problems.
Identify systemic reliability, scalability, security, or architectural gaps across the platform and drive cross-team initiatives to resolve them.
Partner with product, security, and engineering leadership to translate business requirements into architecture decisions, clear engineering specifications, and sequenced delivery plans.
Architect high-throughput ingestion and telemetry pipelines that reliably collect data from large network device fleets (e.g., gNMI/gRPC, NETCONF, SNMP streams).
Design event streaming architectures using Kafka or Kinesis with well-defined delivery semantics (at-least-once / exactly-once), schema enforcement and evolution, and backpressure handling.
Define the time-series and storage strategy (InfluxDB, TimescaleDB, or equivalent), including partitioning, retention, archival, and query performance under production load.
Design RESTful and gRPC APIs that expose platform data to internal consumers and external integrations, evaluated by latency SLAs, uptime, and adoption by downstream teams.
Build production-quality services, prototypes, and reference implementations in Go and/or Rust (or another production systems language), setting the bar for code quality and test coverage.
Review critical designs and code across teams to ensure correctness, performance, and operability.
Establish the observability architecture — structured logging, distributed tracing, and metrics (OpenTelemetry, Prometheus) — so production issues can be diagnosed and resolved within defined SLOs.
Define multi-tenant isolation, access control, and data-governance patterns that meet security, compliance, and data residency requirements.
Guide incident response for complex production issues, participate in on-call escalation, and drive systemic improvements tracked through post-mortems.
Set the multi-cloud deployment architecture for containerized workloads on Kubernetes, with infrastructure-as-code (Terraform) across AWS, GCP, and Azure, meeting platform availability and cost targets.
Mentor and coach Senior, Staff, and Senior Staff engineers; raise the bar on engineering standards, code review culture, and design practices.
Act as a cross-organizational technical authority on distributed systems and data infrastructure across IonQ.