Senior AI Engineer (f/m/d)

The AI Platform Team at Awin enables teams to build, ship, and operate AI-powered products safely, consistently, and efficiently. The team focuses on shared platform and enablement layers for AI development across the company, including reusable services, internal APIs and SDKs, platform patterns, observability, evaluation support, guardrails, cost visibility, and practical guidance to help teams move from experimentation to production with confidence.

• Strong software engineering fundamentals and experience building production systems
• Strong experience in backend and platform engineering
• Strong system design and architecture skills, especially for shared services or internal platforms
• Practical experience owning systems in production, including deployment, monitoring, support, and incident handling
• Strong understanding of reliability, observability, and operational excellence
• Practical experience with cloud environments and modern release engineering practices
• Experience designing reusable APIs, libraries, SDKs, or internal engineering capabilities
• Good practical experience with Python and/or JavaScript / TypeScript
• Experience building or contributing to AI- or LLM-powered systems in production
• Good understanding of LLM integration patterns, model APIs, prompts, and the engineering trade-offs involved in AI systems
• Good understanding of how to make AI systems observable, testable, and ready for production
• Comfortable working across the full lifecycle of a service, from design and implementation to deployment, support, and improvement
• Good understanding of information security and how to design platform capabilities with security in mind
• Comfortable applying unit testing, continuous integration, and continuous deployment
• Strong communication skills, both synchronous and asynchronous
• Comfortable working through ambiguity and helping shape technical direction where the path is not fully defined
• A platform mindset: able to think beyond one team or one feature and design for reuse, clarity, and long-term maintainability

Nice to have:

• Experience building internal developer platforms or shared engineering tooling
• Experience with AI platform architecture, model access layers, orchestration patterns, or reusable AI infrastructure
• Experience with AI observability tools such as LangSmith or similar tracing or evaluation platforms
• Familiarity with evaluation workflows, regression checks, and quality gates for AI systems
• Experience with cost visibility, usage attribution, or FinOps-style patterns for AI workloads
• Experience working in environments where multiple teams consume shared services
• Experience improving developer experience through templates, examples, SDKs, or documentation
• Experience introducing standards in a way that improves quality without creating unnecessary process

• Design, build, and evolve shared AI platform capabilities used by multiple teams
• Define and improve platform architecture, technical standards, and recommended patterns for AI development
• Build and maintain reusable internal APIs, SDKs, templates, and reference implementations
• Improve the reliability, scalability, and operational maturity of platform-owned services
• Strengthen CI/CD, release engineering, cloud/runtime patterns, and service lifecycle practices for the platform
• Improve platform observability through better tracing, monitoring, debugging, and production feedback loops
• Help define what production-ready AI services should look like from an engineering and operational perspective
• Work closely with product teams to understand repeated needs and turn them into reusable platform capabilities
• Make pragmatic build-vs-buy decisions, preferring simple and durable solutions over unnecessary complexity
• Collaborate with Architecture, Security, Product, and engineering teams to ensure the platform is practical, safe, and easy to adopt
• Write clean, secure, well-tested code and contribute to strong engineering practices across the team
• Mentor other engineers and contribute to technical direction, knowledge sharing, and platform thinking within the team