# Applied AI Engineer
High-impact engineering role focused on building foundational systems that power AI and machine learning across an organization. Work at the intersection of platform engineering and applied AI, designing infrastructure that enables teams to build, deploy, and operate LLM and ML-powered products at scale.
## Accountabilities:
- Build and enhance platform services such as LLM routing/proxy systems, internal APIs, and reusable AI/ML tooling
- Develop and improve LLM and ML operations capabilities, including observability, monitoring, evaluation, and deployment workflows
- Support the full lifecycle of AI systems, including testing, scaling, optimization, and production reliability
- Collaborate with product, infrastructure, and data teams to ensure consistent and reusable AI development practices
- Contribute to system design decisions that improve performance, cost efficiency, safety, and latency of AI services
- Evaluate and integrate emerging AI models, frameworks, and tools into shared platform capabilities
## Requirements:
- 4+ years of software engineering experience, including work on production systems
- At least 1 year of experience in ML Ops, LLM Ops, or AI/ML infrastructure-related roles
- Experience building backend systems, internal platforms, or developer tooling used by engineering teams
- Strong understanding of the end-to-end ML/LLM lifecycle, including deployment and production operations
- Solid engineering fundamentals with the ability to balance trade-offs across reliability, scalability, latency, cost, and maintainability
- Strong collaboration and communication skills, with a team-oriented mindset
- Familiarity with or willingness to work with TypeScript and Python in backend and platform contexts