Senior Agentic Software Engineer

In VIS (Vehicle Information Solutions), an ETAS organization, we are seeking an experienced and innovative Senior Agentic Software Engineer to develop and deploy our next-generation, production-grade AI systems. In this role, you will be responsible for orchestrating robust Python-based back-end architecture, integrating state-of-the-art Large Language Models (LLMs), optimizing high-performance vector databases, and deploying scalable, secure APIs natively on Microsoft Azure. You will work closely with our Original Equipment Manufacturers (OEM) customers to agree on new requirements, develop plans to deliver solutions using Agile processes, and ensure strict adherence to software quality standards throughout the development lifecycle.
VIS is a global ETAS organization supporting leading automotive OEMs and dealer networks with service information, wiring diagrams, technical knowledge, and digital aftersales solutions. VIS is transforming from a traditional technical-content provider into a Vehicle Intelligence partner, leveraging AI, automation, and automotive expertise to support software-defined vehicles and future workshop experience.
Key Responsibilities
Own problems end-to-end: from understanding the user’s needs through architecture, implementation, verification, and operation.
Deliver implementation primarily through AI coding agents: translate intent into precise specs, constraints, and acceptance criteria, and supervise multiple agent work streams in parallel.
Apply human judgment where it matters most: architecture decisions, trade-offs, edge cases, and critical review of agent output - accountable for correctness, security, and maintainability of everything merged.
Design for verifiability: tests, typed interfaces, CI gates, and evals that allow agent-produced code to be proven correct rather than trusted.
Work across frontend, backend, infrastructure, DevOps, and data topics as the problem requires.
Continuously evolve the personal and team development workflow as models and agent capabilities advance.
Thorough understanding of software engineering fundamentals - architecture, system design, testing strategy, debugging.
Infrastructure and DevOps competence: cloud platforms, CI/CD pipelines, containerization, infrastructure as code, and operating what is built.
Excellent communication skills: expressing intent, requirements, and constraints clearly and unambiguously, in writing and in discussion. Proven ability to build relationships with customers, preferably in the automotive industry.
Strong abstraction skills: decomposing complex problems, choosing the right level of abstraction, and recognizing patterns that generalize across domains.
Hands-on production experience with agentic coding tools (e.g. Claude Code, GitHub Copilot agents), including running several agents in parallel and running agents unattended in automated pipelines.
Product thinking: able to translate user and business intent into specifications precise enough for autonomous execution.
Prompt and context engineering: writing instructions, specs, and repo conventions that agents follow reliably.
Strong verification mindset - treats generated code as untrusted until independently checked.
Adaptability: productive in unfamiliar languages, frameworks, and domains, with security awareness for AI-assisted development (secret handling, prompt injection, supply-chain risks).
Bachelor’s Degree in Software Engineering, Computer Science, or similar field of study.

Employment type
Full-time

Work arrangement
Hybrid