Applied Intuition
Software Engineer - AI Engineering
About this role
Applied Intuition seeks an AI Engineer to build shared AI infrastructure and frameworks powering autonomy and intelligence across its products. You'll work in a startup-like environment within a well-funded company, shipping production AI systems while partnering with customers and internal teams to drive real-world impact.
What you'll do
- Design and deploy shared AI infrastructure, frameworks, and tools across Applied's product suite
- Partner with product teams to identify high-impact AI use cases and move them from concept to production
- Establish company-wide best practices for LLM architecture, safety, evaluation, and deployment
- Build agentic systems including coding agents and AI SRE tooling
- Engage directly with customers and internal stakeholders to understand needs and shape roadmap
What they're looking for
- LLM and agentic architecture expertise
- ML/AI product development and deployment
- Full-stack software engineering
- Production-quality code shipping
- Model evaluation and data pipelines
- Cross-functional collaboration
- Initiative-taking and context-switching
Benefits
- Base salary, equity (options/RSUs), and comprehensive health/dental/vision coverage
- 401(k) retirement with employer match
- Learning and wellness stipends
- Paid time off
- Flexible work arrangements with primarily in-office expectations
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Applied Intuition
Applied Intuition builds autonomous vehicle and defense systems software, including motion planning algorithms, simulation infrastructure, and autonomy integration platforms for aerial and ground platforms. The company is hiring for security engineers, robotics/autonomy software engineers, hardware-in-the-loop specialists, and IT operations professionals to support its growing physical AI operations.
- Website
- appliedintuition.com
Likely interview questions
- Walk us through a recent AI/ML-powered feature you built from idea to production. What were the key technical decisions and tradeoffs?
- Tell us about your hands-on experience with LLMs and agentic systems. What frameworks or approaches have you used, and what did you learn?