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About the Role

Frontier AI is seeking a backend software engineer to own and evolve our internal LLM agent framework. This role involves backend infrastructure, applied AI, agent architecture, model post-training, and evaluation tooling, enabling teams to develop, evaluate, and deploy reliable LLM agents in mission-critical environments.

Responsibilities

Own Anduril’s internal LLM agent framework, including core abstractions, runtime architecture, developer experience, integrations, and reliability.
Support multiple business lines building LLM agents by providing new framework capabilities, implementation guidance, architectural reviews, and best-practice patterns.
Partner with machine learning teams to make model post-training workflows easy to integrate, ranging from supervised fine-tuning to offline RL, online RL, and environment-driven agent improvement.
Design tooling that supports modern agent patterns, including structured tool calling, filesystem-using agents, memory and retrieval, planning loops, subagents, agent graphs, and human-in-the-loop workflows.
Work with partner teams to define comprehensive evaluation suites that measure task success, tool-call correctness, trajectory quality, robustness, regressions, and deployment readiness.
Stay current on emerging agent architecture and evaluation trends, and make pragmatic decisions about which techniques should or should not be adopted internally.

Requirements

Strong backend engineering experience building production-quality platforms, frameworks, APIs, or infrastructure used by other engineers.
Deep expertise in LLM agent framework design, including the tradeoffs between different orchestration patterns such as linear agents, graph-based agents, multi-agent systems, planner/executor loops, and tool-heavy agents.
Experience designing agent evaluation paradigms, including trajectory evaluations, LLM-as-judge workflows, task-success metrics, tool-call correctness checks, rubric-based qualitative grading, adversarial scenario testing, regression eval suites, and human-in-the-loop review.
Familiarity with model post-training workflows such as SFT, preference tuning, reinforcement learning, and environment-based agent training.
Strong judgment around reliability, observability, debugging, and safety for LLM applications deployed in high-stakes settings.
Ability to work directly with partner teams, understand ambiguous product needs, and turn them into reusable platform capabilities.

Skills

Langchain
Claude SDK
Kubernetes
Docker
Distributed systems
Workflow orchestration
ML infrastructure
Defense
Robotics
Command-and-control systems
Autonomy
Operational planning

Salary/Compensations

$220,000—$292,000 USD

Benefits

Highly competitive equity grants
Top-tier benefits for full-time employees
Comprehensive, competitive benefits package (available at little to no cost to employees)

About the Company

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’s Lattice software platform integrates together many sensors into a single cohesive view of the world, providing needed context for our users.
Anduril’s Frontier AI team builds edge-compatible, generative AI systems into the Lattice software platform to provide features and products that improve autonomy and reduce cognitive burden on the warfighter.
Specific applications include but are not limited to automating mission planning, battle-space understanding, voice-control of assets, and enabling higher-levels of autonomy.

Equal Opportunity

Anduril is committed to maintaining the integrity of our Talent acquisition process and the security of our candidates.
Anduril will never solicit payment or demand personal financial details (such as banking information, credit card numbers, or social security numbers) at any stage of our hiring process. Our legitimate recruitment is entirely free for candidates.
Direct from Anduril: If you receive an email from one of our recruiters, it will only come from an @anduril.com address.
Via Agency Partner: If contacted by a recruiting agency for an Anduril role, their email will clearly identify their agency. If you suspect any suspicious activity, please verify the agency's authenticity by reaching out to contact@anduril.com.
Exercise Caution with Unsolicited Outreach: If you receive any communication that appears suspicious, contains grammatical errors, or makes unusual requests, do not engage. Always confirm the sender's email domain is @anduril.com before providing any personal information or clicking on links.
Should you encounter any questionable or fraudulent outreach claiming to be from Anduril, please report it immediately to contact@anduril.com.
To view Anduril's candidate data privacy policy, please visit https://anduril.com/applicant-privacy-notice/.
By submitting your application, you consent to Anduril Industries using a third-party service provider to conduct pre-employment risk, integrity, and due diligence screening and assessing potential risks as part of your application process. This third-party service provider provides risk-intelligence services that may include analysis of sanctions and watchlists, adverse media, public-record information, and other lawful open-source or commercial data sources. This third-party service provider does not act as a consumer reporting agency. Use of this provider helps to ensure compliance with applicable laws and protect technology, intellectual property, and organizational security.