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Senior AI Engineer
Skills
BusinessEvolutionFoundationsLarge Language ModelsPermissionsRepositoriesShared Services
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- 5+ years of hands-on experience in software engineering platform engineering solutions engineering infrastructure engineering or a similar technical role
- Strong ability to design and implement production-ready systems across APIs services integrations and data flows
- Experience working with cloud environments and modern application deployment patterns
- Comfort troubleshooting complex technical issues across infrastructure application logic and third-party integrations
- Prior experience building internal platforms shared services developer tooling or reusable technical foundations
- Strong understanding of system design reliability scalability and security considerations
- Demonstrated ability to take ownership of ambiguous technical problems and drive them from design through implementation
- Experience defining technical patterns processes or standards that other builders rely on
- Practical experience working with AI-powered applications agent architectures LLM-based workflows or adjacent systems
- Strong communication skills and the proven ability to work cross-functionally in a fast-moving environment
- Comfort with ambiguity and a strong builder mentality and a bias toward practical execution
Nice to have
- Hands-on
- Builder mentality
- Cross-functional
- Ambitious
- Practical
Day to day
- Own the design and evolution of core capabilities within the internal AI agent platform to support high-impact business workflows and AI agents
- Define and improve deployment patterns shared services and orchestration approaches that enable complex agent use cases to run reliably
- Partner with business stakeholders to translate strategic goals into scalable AI agent solutions
- Work hands-on with builders to debug issues answer technical questions and unblock day-to-day development while improving the underlying platform
- Investigate failing repositories run code locally and fix infrastructure or environment issues at the root cause
- Build and maintain shared services such as reusable modules integration layers logging patterns and data access approaches
- Drive decisions around observability governance permissions reliability and cost-aware usage to ensure the AI transformation is sustainable and secure
- Help set technical direction for how new capabilities should be designed so durable foundations are created rather than one-off solutions
- Collaborate across engineering and business functions to identify and shape new high-value opportunities for agent-led innovation