Senior Agentic Software Engineer

ETAS•Plymouth, MI

21h

About The Position

ETAS, a subsidiary of Robert Bosch, develops products and solutions for the vehicle software lifecycle, including vehicle basic software, middleware, development tools, cloud-based operations services, cybersecurity solutions, and engineering and consulting. Its Vehicle Information Solutions (VIS) organization serves automotive OEMs and dealer networks with service information, wiring diagrams, technical knowledge, and digital aftersales solutions, and is evolving into a Vehicle Intelligence partner using AI, automation, and automotive expertise. The Senior Agentic Software Engineer will develop and deploy production-grade AI systems. The role involves orchestrating Python-based back-end architecture, integrating large language models, optimizing vector databases, and deploying scalable, secure APIs on Microsoft Azure. The engineer will work closely with OEM customers to define requirements, plan delivery using Agile processes, and uphold software quality standards throughout the development lifecycle. The role emphasizes owning problems from user needs through architecture, implementation, verification, and operation, while delivering software primarily through AI coding agents. The engineer will specify work for agents, supervise parallel work streams, independently verify generated code, and remain accountable for its correctness, security, and maintainability. Work may span frontend, backend, infrastructure, DevOps, and data, with ongoing improvements to development workflows as AI capabilities evolve.

Requirements

Thorough understanding of software engineering fundamentals, including architecture, system design, testing strategy, and debugging.
Infrastructure and DevOps competence, including cloud platforms, CI/CD pipelines, containerization, infrastructure as code, and operating what is built.
Excellent communication skills, including expressing intent, requirements, and constraints clearly in writing and discussion.
Proven ability to build customer relationships; automotive industry experience is preferred.
Strong abstraction skills, including decomposing complex problems, choosing appropriate abstractions, and recognizing patterns that generalize across domains.
Hands-on production experience with agentic coding tools such as Claude Code or GitHub Copilot agents, including running multiple agents in parallel and running agents unattended in automated pipelines.
Product thinking: ability to translate user and business intent into specifications precise enough for autonomous execution.
Prompt and context engineering skills, including writing instructions, specifications, and repository conventions that agents follow reliably.
A strong verification mindset: generated code is treated as untrusted until independently checked.
Adaptability and ability to work productively in unfamiliar languages, frameworks, and domains.
Security awareness for AI-assisted development, including secret handling, prompt injection, and supply-chain risks.
Bachelor’s degree in Software Engineering, Computer Science, or a similar field of study.
Indefinite U.S. work authorization; future work-authorization sponsorship is unavailable.
Successful completion of a drug screen and background check before the start date.

Nice To Haves

Experience building relationships with customers in the automotive industry.

Responsibilities

Own problems end-to-end, from understanding user needs through architecture, implementation, verification, and operation.
Deliver implementation primarily through AI coding agents by translating intent into precise specifications, constraints, and acceptance criteria.
Supervise multiple AI agent work streams in parallel.
Use human judgment for architecture decisions, trade-offs, edge cases, and critical review of agent output; ensure the correctness, security, and maintainability of merged work.
Design for verifiability through tests, typed interfaces, CI gates, and evaluations that establish the correctness of agent-produced code.
Work across frontend, backend, infrastructure, DevOps, and data topics as needed.
Continuously evolve personal and team development workflows as models and agent capabilities advance.
Work with OEM customers to agree on requirements and develop delivery plans using Agile processes.
Ensure adherence to software quality standards throughout the development lifecycle.