Software Engineering Manager (Factory Data)

Title: Software Engineering Manager (Factory Data) Location: Santa Ana, California, United States

ABOUT THE TEAM

Maritime Digital Production (MDP) is the software and digital systems function within Anduril's Heavy Metal division. We build and deploy the full technology stack that powers Anduril's shipbuilding factories: the data infrastructure that makes every machine and sensor visible in real time, the manufacturing execution system (ArsenalOS) that workers and planners use every shift, the scheduling engine that replans production in minutes instead of days, and the AI systems that eliminate manual toil from both the shop floor and business operations.
MDP operates at the boundary between Operational Technology and Information Technology. Our systems live where factory-floor machines, edge compute, and OT networks meet enterprise platforms and cloud infrastructure. We incubate solutions close to the production line, validate them with real operators building real hardware, harden them for reliability and security, and then scale them across multiple sites. The environment is fast, physical, and consequential. When our systems go down, production stops. The output of our work is not a dashboard: it is a ship.
This is not a support function. It is a strategic investment by Anduril in the premise that digitizing the manufacturing lifecycle end-to-end, from engineering definition through scheduling through execution through field feedback, is how Heavy Metal will out-build, out-adapt, and out-scale the traditional defense industrial base. MDP is scaling from a founding team to 70+ engineers across multiple U.S. sites. You will be joining early, working on hard problems with real operational stakes, and shaping how manufacturing software is built at Anduril from the ground up.

ABOUT THE JOB

As Software Engineering Manager for Factory Data, you will lead a team of data and software engineers building the real-time data infrastructure that connects factory PLCs, sensors, and control systems to the Unified Namespace. You will drive technical excellence, hire and develop top engineering talent, and ensure your team delivers high-throughput data pipelines and APIs that downstream consumers—including scheduling systems, AI models, and operational dashboards—depend on where uptime is non-negotiable.

WHAT YOU'LL DO

• Lead, mentor, and grow a team of data engineers and software engineers building Factory Data's real-time ingestion pipelines, time-series databases, and data access APIs.
• Hire exceptional engineering talent, building a high-performing team that balances speed, quality, and operational excellence in a critical data infrastructure role.
• Set technical direction and architectural standards for Factory Data including data pipeline design, time-series database optimization, industrial protocol integration, and API design patterns.
• Partner with manufacturing engineers, factory operators, and downstream consumers (LOKI, Applied Intelligence, ArsenalOS teams) to understand data requirements and ensure your team delivers reliable, high-quality data infrastructure.
• Drive delivery and execution, ensuring your team ships high-throughput data pipelines on time while maintaining production stability and meeting availability SLAs for factory-critical systems.
• Ensure your team writes production-quality code with comprehensive tests, participating in code review and establishing engineering best practices for data systems.
• Own operational excellence for Factory Data including on-call rotations, incident response, data quality monitoring, and continuous reliability improvements.
• Collaborate with infrastructure teams, DevOps/SRE, and downstream engineering teams to ensure seamless integration with edge compute, OT networks, and enterprise systems.
• Deploy and operate systems in factory environments, including edge compute clusters and OT networks, through your team's execution.
• Champion the adoption of AI tooling (coding assistants, automation) and contribute to team engineering practices that improve development velocity.
• Manage performance, provide regular feedback, and create growth opportunities for engineers on your team through coaching, mentoring, and career development.
• Establish and track engineering metrics including data pipeline uptime, ingestion latency, data quality, throughput, and API availability to drive continuous improvement.
• Drive technical decisions on industrial data protocols (OPC-UA, Sparkplug B, Modbus), message broker architecture (MQTT, AMQP, Kafka), and time-series database selection.
• Represent Factory Data in technical discussions, architectural reviews, and cross-team planning to ensure alignment with broader MDP goals.

REQUIRED QUALIFICATIONS

• 8+ years of experience in software engineering building production systems, with at least 2+ years in engineering management or technical leadership roles.
• Proven track record hiring, developing, and retaining high-performing engineering teams in fast-paced environments.
• Deep technical expertise in data engineering with hands-on experience building data pipelines, data infrastructure, or streaming systems.
• Strong technical fluency in modern software architectures, APIs, distributed systems, CI/CD, and cloud or edge infrastructure.
• Experience managing teams building high-throughput, low-latency data systems with high availability requirements.
• Demonstrated ability to balance technical execution with people management, mentorship, and team development.
• Experience managing operational excellence including on-call rotations, incident response, and maintaining production system reliability for data infrastructure.
• Excellent written and verbal communication skills, with the ability to collaborate across engineering, manufacturing, operations, and leadership teams.
• Proven ability to navigate ambiguity, make technical and organizational trade-offs, and drive outcomes without complete information.
• Degree in Computer Science, Information Systems, Engineering, or related technical field, or equivalent practical experience.
• U.S. Person status is required as this position needs to access export controlled data.

PREFERRED QUALIFICATIONS

• Experience in manufacturing, industrial, or OT-adjacent domains (MES, SCADA, PLC integration, factory automation, IoT).
• Background managing teams building real-time data pipelines, streaming systems, or time-series data infrastructure at scale.
• Experience with time-series databases (InfluxDB, TimescaleDB, Prometheus), message brokers (MQTT, Kafka, AMQP), or industrial data protocols (OPC-UA, Sparkplug B).
• Familiarity with OT network infrastructure, edge computing, and deploying data systems in factory environments.
• Experience in hyper-growth startup-like environments, with demonstrated success building teams and scaling data engineering practices.
• Technical background in data pipeline frameworks (Kafka, Flink, Spark Streaming), API gateway patterns, or high-availability distributed systems.
• Experience managing teams that deploy software to edge environments, factory floors, or operational technology networks.
• Familiarity with enterprise systems such as ERP, MES, WMS, or manufacturing planning systems and their data integration requirements.
• Experience with cloud platforms (AWS, Azure, GCP) and hybrid cloud/edge architectures.
• Familiarity with frontier AI tooling, AI coding assistants, and AI-enabled software development workflows.
• Experience in manufacturing industries with hands-on exposure to assembly lines or production environments.
• Background in data quality frameworks, data governance, or observability for data infrastructure.
• Proven ability to set technical standards, drive architectural decisions, and maintain high code quality across a data engineering team.
• Eligible to obtain and maintain a U.S. Secret security clearance.