Applied AI Engineer (all genders)

Description

The team is building AI-native engineers, people who treat AI as a core part of their daily work rather than an add-on.

This is a core engineering role in the fastest-growing part of the market. You will design, build and ship production-grade full-stack software for client programs across industries, with AI tools built into your routine.

Engineers who build agentic depth can move toward the Forward Deployed Engineer program.

The company is a global professional services firm with approximately 791,000 people serving clients in more than 120 countries, combining technology, cloud, data and AI with industry and functional expertise.

Responsibilities

• Build and ship production software across the full stack, including the application layers, APIs and interfaces that connect your code to agentic backends.
• Understand data flows, context handoffs and integration points between your code and AI pipelines.
• Own delivery from design through production support within Agile sprints, working alongside client engineering teams.
• Connect to agentic AI systems and enterprise AI pipelines, including agent architecture and LLM APIs.
• Call AI provider APIs in live code, manage token limits and latency, and build early abstraction layers.
• Use AI coding assistants every day in delivery, showing measurable gains in productivity and output quality.
• Apply AI across testing, debugging, code review and prompt design for development work.
• Check the quality of AI-generated output in your scope, judge its reliability, limits and failure modes, and decide when it is ready for production.
• Set and track KPIs that measure the effectiveness and return of AI-assisted workflows, and report AI productivity and quality results to project stakeholders.
• Contribute reusable components, shared knowledge and internal AI tooling standards for the wider team.

Requirements

• Bachelor's degree in computer science, computer engineering, software engineering or a related field.
• Some exposure to professional software engineering in production, or equivalent evidence from academic work, internships or personal projects you have shipped.
• Working proficiency in at least one backend language: Python, Java or TypeScript.
• Proven hands-on use of AI tools in daily engineering, with examples of solving real problems, refining outputs and improving delivery.
• Direct experience calling LLM APIs in production code, with an understanding of token management, latency and cost trade-offs.
• Basic knowledge of JavaScript, HTML and CSS.
• Familiarity with cloud fundamentals on AWS, Azure or GCP, plus Docker containers and CI/CD pipelines.
• Understanding of Agile delivery basics.
• Experience with SQL or NoSQL databases.
• Ability to validate and improve AI output, with an understanding of AI limits and responsible use.
• Conceptual understanding of agentic systems is required: awareness of orchestration frameworks such as LangChain, LangGraph or equivalents, RAG pipelines, and how full-stack applications connect to agent-based architecture.
• Production experience with agentic systems is preferred.
• Very good German and English language skills.
• Willingness to travel occasionally for business purposes.

Conditions

Hybrid working models are available.

Occasional business travel is required.

Hiring decisions are made without regard to any legally protected characteristic, including age, race, religion, sex, disability, citizenship or sexual orientation.

Benefits

• Structured AI certifications and continuous learning, with access to more than 30,000 training resources.
• Vendor fellowship access inside Anthropic, OpenAI, Microsoft and Google engineering teams, and work with leading AI technologies.
• Flexible working, including hybrid options.
• Mentoring, coaching and defined career paths toward advanced AI and Forward Deployed Engineering roles.
• Varied projects across industries, technologies and enterprise environments, giving broad experience.