Senior Applied AI Engineer (all genders)

Description

You will build AI systems that run in production inside enterprise clients, not demos or pilots that never leave the lab.

The gap between you and this role is practical: you have shipped a multi-agent system to production, you have run an eval harness yourself, and you have handled an agent failure in the middle of the night.

As an Applied AI Engineer (agentic) you design, build and deploy production agentic systems across whole enterprise technology stacks, work alongside client engineers, lead design sessions, and create reusable patterns that carry over between projects.

Demand for AI engineers is rising faster than supply and will keep doing so.

The company is a global professional services firm, so you get breadth across industries, technology stacks and levels of organizational complexity, plus vendor fellowship access within Anthropic, OpenAI, Microsoft and Google engineering teams and a direct route into the Forward Deployed Engineer programme.

Responsibilities

• Design, build and ship end-to-end agentic systems covering multi-agent orchestration, RAG, policy-based routing, tool calls, memory and lifecycle observability.
• Own RAG pipelines: embeddings, chunking, vector search and context window tuning against measurable quality targets.
• Connect several LLM providers (OpenAI, Anthropic, Vertex AI and open-source models) behind one abstraction, with fallback routing and control of tokens, cost and latency.
• Run LLMOps in production: eval harnesses with real quality metrics, prompt versioning, observability tools such as LangSmith or Braintrust, and cost and safety monitoring.
• Work inside client engineering teams through workshops, proofs of concept, code-together sessions and architecture walkthroughs to design, prototype and deploy agentic solutions.
• Create reusable patterns, accelerators and playbooks that help the next engagement start faster.
• Define metrics for agent accuracy, latency, safety and cost-effectiveness, and present results and recommendations to client stakeholders in business terms.

Requirements

• Extensive years of software engineering in production environments.
• Hands-on experience designing and deploying agentic AI in production: non-negotiable.
• Production-depth experience with agent orchestration frameworks such as LangGraph, CrewAI, AutoGen or equivalent, not tutorial-level work.
• Production code that calls LLM APIs (OpenAI, Anthropic, Vertex AI), including provider abstraction and trade-offs between tokens, latency and cost.
• Ownership of RAG pipelines: embeddings, chunking strategy, vector databases and context engineering.
• Working knowledge of LLMOps: eval harness design, prompt versioning and production observability.
• Cloud-native skills: Kubernetes, Docker, microservices, serverless, CI/CD and IaC (Terraform or Helm).
• Strong Python; Java or an equivalent backend language is acceptable. Experience debugging and observing production systems.
• Quality of experience counts more than years: someone who shipped three production agentic systems in four years is preferred over a generalist with passive AI exposure.
• Very good German and English.

Conditions

Occasional business travel is required.

Hybrid work options are available.

Hiring decisions are made without regard to age, race, religion, colour, sex, gender identity or expression, sexual orientation, disability, veteran status, national origin, ancestry, genetic information, marital status, citizenship or other legally protected characteristics.

Benefits

• Work on AI solutions for large global enterprises across industries, technologies and complex transformation programs.
• Access to advanced AI ecosystems and strategic partnerships with major cloud and AI platforms, working alongside highly experienced engineers.
• Paths into technical leadership and specialist tracks, plus mentoring and ongoing learning through certifications and advanced programs.
• Flexible working models and hybrid options that support a sustainable work-life balance.
• Competitive pay with bonus programs, employee share purchase opportunities and other role-specific benefits where applicable.