Staff Systems Engineer, Applied Intelligence

Anduril Maritime delivers platforms, systems, and integrated effects in the maritime domain. Our autonomous vehicles (sub-surface and surface) are the cornerstone of these capabilities, and we continually strive to push the boundaries of the possible in terms of endurance, autonomy and mission capability. The Maritime team develops and maintains core products and payloads, and adapts and applies those products to serve a wide variety of defense, IC and commercial customers in US and international markets.

We are seeking a Staff Systems Engineer, Applied Intelligence to join the Applied Intelligence team within Maritime Digital Production. You will own and mature a portfolio of digital technology development projects—taking promising capabilities from concept through deployment and stabilization in live production environments. This role focuses on architecting, integrating, and hardening digital systems (software and hardware) that directly improve manufacturing throughput, quality, and safety.
You’ll work across software, data, and operational technology domains to deploy resilient, event-driven systems that link R&D innovations to the real-world factory floor. Your work will ensure new capabilities land fast, scale safely, and perform reliably as part of the broader digital production ecosystem.

• Own and manage a portfolio of digital projects, driving each from prototype through production readiness and operational transition.
• Architect, integrate, and operate systems that connect digital and hardware capabilities into manufacturing and production workflows.
• Design and deploy event-driven, containerized systems with strong observability, version control, and rollback capabilities.
• Translate R&D prototypes into production-grade, supportable services with defined SLOs, telemetry, and auditability.
• Develop and maintain data infrastructure for ingestion, transformation, and system telemetry—integrated with unified namespaces and event brokers.
• Collaborate with software, data, manufacturing, and operations teams to define and govern integration contracts, APIs, and schemas for interoperability and safety.
• Implement automation pipelines for deployment, monitoring, and recovery to ensure continuous availability and resilience.
• Work with digital, manufacturing, and corporate technology teams to align on architecture, data governance, and compliance standards.
• Contribute to the design of time-series and ontology-based data models that structure and contextualize operational and digital systems.
• Lead field deployments, ensuring new systems stabilize under operational conditions through telemetry tuning and reliability engineering.

• Strong stakeholder management experience with the ability to align technical and operational teams across multiple domains.
• 7+ years of experience in systems or infrastructure engineering, ideally spanning IT, OT, and hardware integration.
• Demonstrated experience owning and delivering digital technology projects into production environments.
• Proven ability to design, deploy, and maintain distributed systems across hybrid cloud and on-prem architectures.
• Proficiency with containerization and orchestration technologies (Docker, Kubernetes).
• Experience with infrastructure-as-code and automation frameworks (Terraform, Ansible, or equivalent).
• Familiarity with event-driven architectures, IoT systems, and message brokers (MQTT, Kafka, NATS).
• Strong foundation in data engineering, time-series data management, and semantic/ontology-driven system modeling.
• Scripting or programming ability for automation and diagnostics (Python, Bash, PowerShell).
• Strong understanding of networking, security, and access control in regulated environments (NNPI/ITAR preferred).
• Excellent problem-solving and documentation skills; proven ability to deliver under operational constraints.
• Eligible to obtain and maintain an active U.S. Secret security clearance.

• Experience integrating digital or hardware systems into production and manufacturing environments.
• Background in industrial, cyber-physical, or mission-critical system engineering.
• Familiarity with CI/CD pipelines, observability stacks (Prometheus, Grafana, ELK), and telemetry-driven reliability engineering.
• Experience working with schema registries, API contracts, and data model governance frameworks.
• Understanding of digital twin architectures, system safety models, or human-in-the-loop verification.
• Proven ability to lead field stabilization efforts and scale capabilities from pilot to enterprise deployment.