Anduril

4 weeks ago

Software Engineer, Agent Platform

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Backend-focused role building and evolving Anduril's internal LLM agent framework. You’ll design scalable infrastructure, integrate model post-training workflows, and create tooling for advanced agent patterns to deploy reliable, high-stakes AI in mission-critical environments.

Location: Washington

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Key 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.

Pay and Benefits

Salary: USD 220,000 - 292,000 annually

Key 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 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.

Experience:DefenseAILLMAutonomy

Skills:CollaborationCommunicationProblem-solvingSystems thinkingDebugging

Languages:English

Tech Stack:KubernetesDockerLangChainDeepAgentsClaude SDKLLMSFTRLOffline RLOnline RL

Company Brief

Anduril

Designs and builds advanced defense systems combining autonomous aircraft, sensors, and AI-driven software for military and national security applications, focused on modernizing battlefield capabilities and distributed sensing.

Industry: Defense Technology

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series E+

Headquarters: Costa Mesa, United States

Founded: 2017

Website LinkedIn

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Anduril

4 weeks ago

Software Engineer, Agent Platform

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Location: Washington

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Key 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.

Pay and Benefits

Salary: USD 220,000 - 292,000 annually

Key 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 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.

Experience:DefenseAILLMAutonomy

Skills:CollaborationCommunicationProblem-solvingSystems thinkingDebugging

Languages:English

Tech Stack:KubernetesDockerLangChainDeepAgentsClaude SDKLLMSFTRLOffline RLOnline RL

Company Brief

Anduril

Industry: Defense Technology

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series E+

Headquarters: Costa Mesa, United States

Founded: 2017

Website LinkedIn