Applied AI Engineer
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an Applied AI Engineer based in Germany.
This is a high-impact engineering role focused on building the foundational systems that power AI and machine learning across an entire organization. You will work at the intersection of platform engineering and applied AI, designing the infrastructure that enables teams to build, deploy, and operate LLM and ML-powered products at scale. Your work will shape how AI systems are accessed, monitored, evaluated, and governed in production environments. Rather than focusing on a single application, you will create shared capabilities used across multiple engineering and product teams. The environment is fast-moving, highly collaborative, and deeply technical, with a strong emphasis on reliability, scalability, and developer experience. This role is ideal for engineers who enjoy solving complex systems problems and enabling others to build better AI products.
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
Benefits:
- Competitive compensation package including base salary, variable pay, and equity
- Comprehensive healthcare coverage (medical, dental, and vision)
- Flexible working arrangements with a remote-first or hybrid-friendly culture
- Unlimited paid time off and generous parental leave policies
- Learning and development budget to support continuous growth
- Home office stipend and equipment support
- Mental health and wellness resources
- Opportunity to work on cutting-edge AI infrastructure used at scale
