AI Engineer (w/d/m)

About Us

We are a specialized AI Engineering and FullStack team building productive LLM/Agent systems for our clients — no PoC theater, no PowerPoint decks, no "Slide Architects". We advise as partners at eye level and deliver software that runs in production.

You can solve problems here without being restricted by titles or fixed role definitions — they don't exist here. Our jobs are not rigid; they serve only as a guide. You won't be limited to (your) job but will develop across AI Engineering, Backend, Platform, and Consulting. Your individual goals, ideas, and strengths are paramount. You proactively shape your career at Arcode.

Important: As we work closely with our clients in the DACH region (Finance, Insurance, Public Sector, Industry), excellent German language skills (ideally native, at least C1) are mandatory — fluent English is a prerequisite.

Responsibilities

What awaits you

As an AI Engineer (w/d/m), you won't just write notebooks and prompts; you'll build productive GenAI systems: Agents, RAG pipelines, LLM-driven workflows — end-to-end from use-case workshops to production deployment.

You'll work in cross-functional, agile teams on client projects, encountering the entire modern GenAI stack: pydantic-ai, LangChain/LangGraph, MCP (Model Context Protocol), OpenAI, Anthropic Claude, Azure AI Foundry, AWS Bedrock.

Together with your team, you'll advise our clients on use-case identification, architectural decisions (RAG vs. Fine-Tuning, Agent Design, Tool Use, Memory), effort estimations, and the selection of suitable methodologies — you'll be involved in the entire AI lifecycle.

You'll analyze client requirements, design and implement agent-based solutions, RAG pipelines over enterprise data, structured LLM outputs (pydantic schemas, tool use), and ensure good documentation.

You'll always keep an eye on quality — and with AI, that means systematic evals, regression tests against gold sets, hallucination monitoring, cost-per-inference tracking, prompt versioning, and observability for agent traces (OpenTelemetry, Langfuse, Phoenix).

You'll use modern, automated approaches and AI-native developer workflows (Claude Code, Cursor, GitHub Copilot) to optimize code, detect errors, and find innovative solutions — we live "AI-native", not just AI-for-clients.

You'll integrate your LLM/Agent components cleanly into existing backend and frontend architectures (Python/FastAPI, Node.js/TypeScript, Java, React/Angular) and ensure clean handoffs to the platform side (Kubernetes, ArgoCD, MongoDB/pgvector, AWS/Azure).

Qualifications

What you should bring

Thanks to your relevant professional experience, you approach AI Engineering hands-on — you don't just talk about LLMs, you build with them.

Excellent to native German language skills are MANDATORY, as we work closely with clients in the DACH region.

You enjoy working agilely but also understand that not all clients are as familiar with or appreciate agility (and especially GenAI Engineering) as we are.

You have a Bachelor's or Master's degree or a comparable professional qualification in Computer Science, Information Technology, Electrical Engineering, Physics, Mathematics, Artificial Intelligence, Data Science, or another natural or engineering science — or you convince us with a strong track record instead of certificates.

You are a team player, value open communication, enjoy learning from others, and share your knowledge — especially in the LLM field, where the tooling landscape changes every three months.

You want to work on exciting client projects and have good knowledge in some of these technologies:

• AI / GenAI: Python, pydantic, pydantic-ai, LangChain / LangGraph, MCP, OpenAI / Azure OpenAI APIs, Anthropic Claude, Azure AI Foundry, AWS Bedrock, Hugging Face Transformers, PyTorch, Embeddings & Vector DBs (pgvector, MongoDB Atlas, Weaviate, Pinecone, Qdrant), RAG Patterns, Prompt Engineering, Agent Evals (Langfuse, Phoenix, ragas)
• Backend / FullStack: Python (FastAPI), Java/Spring or Quarkus, Node.js/TypeScript (Express, NestJS), React, Angular, MongoDB, PostgreSQL, REST/GraphQL
• Platform / DevOps: Docker, Kubernetes, ArgoCD, GitLab CI / GitHub Actions, AWS, Azure, MLOps, Observability (Prometheus, Grafana, OpenTelemetry)
• AI-native Tooling: Claude Code, Cursor, GitHub Copilot, Codium — you use them daily yourself and can show clients how to use them productively.

Consulting suits you, and you can imagine training our clients technologically and/or methodologically (LLM use-case workshops, agent architecture reviews, AI governance consulting for regulated industries). For this, you bring strong communication skills and good German language proficiency.

Bonus, not a must: Own publications / open-source contributions / conference talks in the AI field, experience with Machine Unlearning, Privacy Auditing, BaFin/EU-AI-Act, or Edge AI.

Benefits

What we offer you

Whether remote or in the office – you decide how and where you work, as long as it's coordinated with your project and team. The default is remote, with on-site days at the client's as needed (typically every 2 weeks).

OffProject Time – You spend most of your time on client projects. Approximately 20% of your working time is available for further training, research, open-source contributions, conference talks, community engagement, or internal AI initiatives — we actively publish (ICPR 2026, IPDPS 2026, NeurIPS 2026 in preparation) and want you to be part of it.

You enjoy project and client diversity across finance, insurance, public sector, and industry, and work self-organized and independently with the latest LLM and agent technologies in cross-functional teams.

You choose your complete hardware, including OS — private use included. Plus a dedicated AI tooling budget (Claude/ChatGPT/Cursor/Copilot Pro licenses, API credits for experiments) — you should work with the best tools, not the cheapest.

You'll find yourself in an environment that takes family-friendliness, trust, freedom, knowledge sharing, participation, and a culture of learning from mistakes truly seriously — in a field where "making mistakes" is the only way to get GenAI systems productive.

In addition to flexible trust-based working hours, you have 30 days of vacation, special leave, purchasable vacation, and Christmas and New Year's Eve are generally non-working days. You can also take a sabbatical.

For Freelancers: Alternatively, €80 – €110 / hour depending on profile, clear project assignment, fair forecast communication.

We look forward to hearing from you!