# Software Engineer, Data Engineering, LOKI **Company**: Anduril Industries **Location**: Santa Ana, California **Experience**: senior **Job type**: full-time **Salary**: $166,000-$220,000 USD **Category**: Engineering **Industry**: Technology **Apply**: https://job-boards.greenhouse.io/andurilindustries/jobs/5194568007?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply **Canonical**: https://yubhub.co/jobs/job_13c5dbd5-25c ## Description Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. 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. As a Software Engineer, Data Engineering on the LOKI initiative, you will develop the data systems that power intelligent manufacturing scheduling and optimization. ## Responsibilities - Build high-performance data processing systems that replan production schedules in under 10 minutes when disruptions occur, using constraint solvers and numerical optimization techniques. - Partner with manufacturing engineers and factory operators to understand production workflows and translate them into software requirements. - Write production-quality code with comprehensive tests, participating in code review and architectural discussions. - Design and implement data access layers for computational geometry operations, enabling efficient extraction of features, dependencies, and manufacturing sequences from CAD models. - Develop graph algorithms that model manufacturing dependencies, resource constraints, and optimization objectives across complex assembly operations. - Integrate data from PLM, ERP, MES, and CAD/CAM systems to create a unified data foundation for scheduling and optimization algorithms. - Deploy and operate your systems in factory environments, including edge compute clusters and OT networks. - Implement and optimize constraint solvers (e.g., MIP, CP, SAT) and numerical optimization algorithms for production scheduling under real-world constraints. - Leverage AI tooling (coding assistants, automation) in your development workflow and contribute to team engineering practices. - Join an on-call rotation supporting production factory systems. - Monitor and optimize the performance of scheduling algorithms to ensure sub-10-minute replanning times at production scale. ## Required Qualifications - 3+ years of experience in a software engineering role building production systems, ideally in a fast-paced environment. - Deep expertise in data engineering with strong foundations in algorithms, data structures, and computational complexity. - Strong technical fluency in modern software architectures, APIs, distributed systems, CI/CD, and cloud or edge infrastructure. - Proficiency in programming languages used for data engineering and numerical computing (e.g., Python, Java, Scala, C++, Rust). - Experience with computational geometry, graph algorithms, or numerical optimization techniques. - Strong understanding of data architecture principles and best practices for handling large-scale datasets. - Experience building systems that must operate reliably under real-world operational constraints (high availability, low latency, or constrained environments). - Strong problem-solving skills and ability to translate complex manufacturing problems into algorithmic solutions. - Excellent written and verbal communication skills, with the ability to collaborate across engineering, manufacturing, and operations teams. - Degree in Computer Science, Information Systems, Engineering, Mathematics, Operations Research, 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). - Experience with constraint solvers (OR-Tools, Gurobi, CPLEX, Z3) or numerical optimization frameworks (SciPy, JuMP, Pyomo). - Background in operations research, scheduling algorithms, or discrete optimization applied to manufacturing or logistics. - Experience with graph databases (Neo4j, JanusGraph) or graph processing frameworks (NetworkX, Apache TinkerPop). - Familiarity with frontier AI tooling, AI coding assistants, and AI-enabled software development workflows. - Experience in hyper-growth startup-like environments, with demonstrated success balancing speed, ambiguity, and long-term system health. - Familiarity with enterprise systems such as ERP, MES, WMS, PLM, or manufacturing planning systems. - Experience with real-time data processing and stream processing technologies (e.g., Kafka, Flink). - Experience in manufacturing industries with hands-on exposure to assembly lines or production environments. - Knowledge of Bill of Materials (BOM) structures, manufacturing routing, and production planning concepts. - Eligible to obtain and maintain a U.S. Secret security clearance. ## Skills ### Required - data engineering - algorithms - data structures - computational complexity - modern software architectures - APIs - distributed systems - CI/CD - cloud or edge infrastructure - Python - Java - Scala - C++ - Rust - computational geometry - graph algorithms - numerical optimization techniques ### Nice to have - manufacturing - industrial - OT-adjacent domains - MES - SCADA - PLC integration - factory automation - IoT - constraint solvers - numerical optimization frameworks - operations research - scheduling algorithms - discrete optimization - graph databases - graph processing frameworks - frontier AI tooling - AI coding assistants - AI-enabled software development workflows - ERP - WMS - PLM - manufacturing planning systems - real-time data processing - stream processing technologies --- Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/andurilindustries/jobs/5194568007?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)