Software Engineer - AI Engineering
Confirmed live in the last 24 hours
Applied Intuition
Job Description
About Applied Intuition
We are an in-office company, and our expectation is that employees primarily work from their Applied Intuition office 5 days a week. However, we also recognize the importance of flexibility and trust our employees to manage their schedules responsibly. This may include occasional remote work, starting the day with morning meetings from home before heading to the office, or leaving earlier when needed to accommodate family commitments.
Meet our software engineers!
About the role
We are looking for an AI engineer to join a small, high-impact team building the AI capabilities, agent frameworks, and app platform that power every Applied product and the workflows our own engineers rely on daily. This is a 0 to 1 role with real customer demand already behind it and the potential to scale into a major new business line. You’ll operate like a startup within a larger, well-resourced company – with the freedom to experiment, ship fast, and work directly with customers.
At Applied Intuition, you will:
- Design and ship the shared AI infrastructure, frameworks, and tooling that power AI capabilities across Applied’s products and toolings.
- Partner with product teams to identify the highest-leverage AI use cases and take them from idea to production.
- Serve as a GenAI/LLM expert across the company – owning best practices for architecture, safety, evaluation, and deployment.
- Design, build, and ship agentic systems such as background coding agents, AI SRE tooling
- Work directly with customers to understand their needs, demo capabilities, and shape the product roadmap. Both external customers and internal teams are your customers.
We're looking for someone who has:
- A Bachelor's degree in Computer Science, Software Engineering, or equivalent
- 3+ years of experience building and deploying AI/ML-powered features & products
- Hands-on proficiency working with LLMs and agentic architectures.
- Strong software engineering fundamentals and a bias toward shipping production-quality code quickly
- Comfort working across the stack, from backend infrastructure to APIs to frontend work.
- A collaborative mindset and genuine enjoyment of customer interaction – both with external customers and internal teams who depend on your work.
- Proven ability to take initiative and context-switch across multiple high-priority projects in a fast-paced environment
Nice to have:
- Practical ML literacy – you understand model evaluation, data pipelines, and the tradeoffs between app
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