Senior Agentic Systems Engineer (d/f/m)

This is a great opportunity to join one of our dealer-facing teams at mobile.de and help car dealers manage inventory more effectively, act on data-driven recommendations, and automate daily workflows by building agentic solutions that make dealers more efficient in their day-to-day work.
We are a cross-functional team of frontend, backend and full‑stack engineers, a product manager, a UX designer, and (soon) a data engineer, working closely with data scientists, an MLOps engineer and currently supported by AI engineers partnering with us as contractors. As a Senior Agentic Systems Engineer, you’ll contribute to our agent platform and work closely with other engineers to integrate tools and workflows into the product. You’ll help shape product decisions and engineering practices that improve performance, maintainability, and developer experience, while seeing your work used by thousands of car dealers.

Who you are

• Passionate about AI and agentic platforms: You are deeply interested in the future of AI-driven systems and excited to pioneer their use at scale.

• Innovative and entrepreneurial: You proactively identify opportunities for agentic automation, bring in new ideas, and drive them to execution.

• Strong communicator and collaborator: You can bridge technical and business perspectives, explain complex agentic concepts clearly, and inspire others to follow your lead.

• Committed to continuous learning: You stay current on AI, LLM, and agentic trends, and are eager to upskill yourself and your team.

What you'll do

• Design, build, and evolve agentic platforms: Architect and implement robust, scalable agent-based systems on AWS AgentCore & Bedrock and/or Google Vertex AI Agent Engine, and modern cloud-native infrastructure.

• Drive AI-first engineering: Champion the adoption of agentic and generative AI technologies across the product lifecycle, leveraging frameworks like LangChain and LangGraph for tool orchestration and intelligent workflow automation.

• Integrate and optimize multi-system workflows: Develop and maintain integrations between agentic platforms, K8s services (via MCP Server), and recommendation engines, ensuring secure, efficient, and observable cross-environment operations.

• Enable secure, compliant, and observable AI: Embed strong runtime policy enforcement, guardrails, and observability into agentic workflows—ensuring compliance with regulatory, privacy, and ethical standards (including the EU AI Act).

• Own end-to-end delivery: Lead the full lifecycle of agentic solutions, from ideation and prototyping to production deployment and monitoring, with a strong focus on measurable impact and continuous improvement.

• Collaborate and inspire: Work closely with cross-functional teams (Product, Data, Platform, Legal, Privacy) to deliver value and foster a culture of AI literacy, knowledge sharing, and responsible innovation.

• Stay ahead of the curve: Continuously scout, evaluate, and introduce new agentic and AI technologies, sharing best practices and mentoring peers to accelerate company-wide AI adoption.

Hard skills & experience

• Agentic platform engineering: Hands-on experience designing, developing, and operating agentic systems using frameworks such as AWS AgentCore, Google Vertex AI, Bedrock, LangChain, LangGraph, AutoGen, CrewAI or similar.

• Cloud-native development: Proficient in AWS infrastructure (VPC, Lambda, S3, IAM, CloudWatch) or their Google Cloud Platform equivalents, with experience in cross-account integrations, Terraform, and Kubernetes.

• 3+ years of professional experience in software engineering

• Programming expertise: Strong coding skills in Python and/or Java, with a track record of building production-grade backend services and APIs.

• System integration: Experience integrating agents with microservices, recommendation engines, and vector databases (e.g., S3 Vector, OpenSearch), ideally in a multi-environment setup.

• Observability, evaluation and compliance: Familiarity with implementing observability, evaluation frameworks (for agents and prompts), runtime guardrails, and compliance controls for AI/agentic workflows.

• FinOps: Ability to provide reliable cost estimations and ensure effective cost controls

• AI adoption and literacy: Demonstrated use of AI-powered development tools (e.g., code assistants, automated testing), and a commitment to responsible and innovative AI adoption.

• Prompt engineering: Demonstrated ability to design, refine, and optimize prompts for large language models and agentic workflows, including multi-step reasoning, tool use, and robust handling of ambiguous or incomplete user input.

• Bonus: Experience with RAG (retrieval-augmented generation), knowledge base design, and secure, scalable agentic product deployments in regulated environments.