AI Automation Engineer

The Employee Experience Team improves the employee experience by turning operational needs into reliable, scalable digital services and automation. In this role, you will take end-to-end ownership of AI-enabled employee services: from working with domain experts and shaping ambiguous problems to designing, building, evaluating, deploying, and continuously improving solutions in production.

What you'll do

• Partner with business and technical teams to understand workflows, constraints, risks, failure modes, and desired outcomes before shaping solutions.
• Own the technical direction, implementation, reliability, maintenance, and continuous evolution of AI-enabled employee services.
• Design and build production-ready AI applications using suitable patterns such as retrieval, structured outputs, tool use, document processing, and multi-step workflows.
• Define appropriate human-review and escalation points for sensitive, uncertain, exceptional, or policy-dependent decisions.
• Integrate AI-enabled workflows with enterprise systems, APIs, data sources, and operational processes through reliable interfaces and secure data flows.
• Establish evaluation approaches from the outset, including representative test cases, quality criteria, risk scenarios, release thresholds, and regression checks.
• Build and operate the surrounding production software, including data models, background processing, automated testing, delivery pipelines, observability, and incident response.
• Monitor quality, safety, latency, cost, adoption, and business outcomes, using production evidence to continuously improve the system and its underlying engineering patterns.

What you'll need

• Senior-level software engineering experience, with strong system-design skills and experience delivering reliable, scalable applications in production.
• Hands-on experience taking at least one AI-enabled application beyond the prototype stage into production, including implementation, evaluation, deployment, and operation.
• Strong backend or full-stack engineering fundamentals, including APIs, data modelling, asynchronous processing, automated testing, debugging, delivery pipelines, observability, and maintainable code.
• Practical experience with production LLM applications, including prompt and context engineering, structured outputs, retrieval-augmented generation, and evaluation approaches.
• Sound judgement in choosing when AI adds value and when deterministic software or human decision-making is more appropriate, reliable, or efficient.
• Strong ownership, structured problem-solving, and collaborative working skills, with the ability to turn ambiguous needs and operational constraints into pragmatic technical solutions.
• Working knowledge of privacy, security, access control, hallucination risk, latency, reliability, model selection, cost, tool-calling, and multi-step or agentic workflows; fluency in English.

What they offer

• Competitive salary package and bonus.
• Hybrid work model with three days on-site per week, 30 days vacation, and 10 days work-from-abroad per year.
• Dedicated learning time, online courses, and structured career development through ScoutAcademy.
• Professional family service and childcare support.
• Subsidized public transport or Job Bikes, pension scheme with employer subsidy.
• Modern barrier-free Berlin office with gym, napping room, rooftop terrace, and weekly massage therapist.