Founding AI Engineer
Skills
Cloud InfrastructureEnterprise SoftwareFailure ModesPipelinesPythonApplied AILLM Applications
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Proven experience deploying applied AI systems into production and owning them through real-world usage
- Experience taking LLM-powered applications from prototype to production where accuracy and reliability matter
- Strong background building applied AI systems rather than conducting ML or model research
- Deep understanding of modern agentic AI architectures and workflows
- Expertise with evaluation frameworks guardrails and AI system reliability
- Experience identifying failure modes and designing robust mitigation strategies
- Strong Python development skills and experience building production-grade AI applications
- Entrepreneurial mindset with the ability to work independently and make architectural decisions
Nice to have
- Entrepreneurial mindset
- Independent ownership
- Architectural decision-making
- Production focus
- Reliability mindset
Day to day
- Own the intelligence layer of the platform from end to end
- Design and build AI systems that power reasoning learning loops reliability and evaluation frameworks
- Define the AI architecture from the ground up and shape the future of AI-powered enterprise software