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.

Senior Agentic Software Engineer

Responsibilities

Benefits

Company

BoschGroup

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