Generative AI Integration Engineer

Anduril Industries
Costa Mesa, California, United StatesPosted 4 April 2026

Job Description

Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years. Anduril is developing and deploying an integrated system to make UxVs highly effective through the entire mission lifecycle. From fleet management, to mission planning, live execution, and integrations into other DOD systems, Lattice is enabling the military to fight at scale with robots across all domains. Anduril is leveraging AI across all aspects of this lifecycle to reduce the barrier to entry for new operators, and increase the scale at which operators can leverage Lattice. Your Job is to design, implement, and evolve the means by which Agents interact with classical software systems. You will contribute to test and eval infrastructure, deployment software, agent tool calling, prompt engineering, and other agent techniques in order to achieve best-in-class performance with frontier and edge deployed models. You will increase the performance and quality of agentic interaction patterns, and you will expand the surface area by which Agents can interact with the overall Lattice system. - good to ship Required Qualifications Demonstrated deep knowledge of the implementation and use of LLM’s Experience integrating agents into classical systems Strong programming skills in Python or other core languages (Java, Go etc) PhD or Master’s degree in Computer Science, Robotics, Machine Learning, or a related field, or equivalent practical experience. Preferred Qualifications Experience with simulation or real-world validation for autonomous vehicles is highly desirable Novel application track record and experience including first author publications, participation in peer reviewed conferences, contribution to open source projects, and demonstrated contribution to the ML and AI community. Experience in multi-modal sensor data processing (e.g., cameras, LiDAR, radar). Familiarity with ML Ops best practices, including model versioning and reproducible research pipelines. Familiarity with C/C++ is a plus. General software engineering experience solving motion planning or related robotics problems. US Salary Range $191,000 $253,000 USD The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Anduril's total compensation package. Additionally, Anduril offers top-tier benefits for full-time employees, including: Healthcare Benefits US Roles: Comprehensive medical, dental, and vision plans at little to no cost to you. UK AUS Roles: We cover full cost of medical insurance premiums for you and your dependents. IE Roles: We offer an annual contribution toward your private health insurance for you and your dependents. Additional Benefits Income Protection : Anduril covers life and disability insurance for all employees. Generous time off : Highly competitive PTO plans with a holiday hiatus in December. Caregiver Wellness Leave is available to care for family members, bond with a new baby, or address your own medical needs. Family Planning Parenting Support: Coverage for fertility ... (truncated, view full listing at source)
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