Build Scalable AI Automation Solutions for Next-Gen Automotive Software
Who We Are
The Quality Assurance team is building next-generation AI-driven solutions that transform how automotive software work products are verified and validated. We design intelligent testing frameworks, AI-powered quality analytics, and automated validation workflows that ensure software artifacts meet the highest quality standards across the development lifecycle
.Our focus is on connecting AI-based testing solutions directly to CI/CD pipelines, enabling continuous, scalable, and data-driven quality assurance.
These systems automatically assess work products, detect anomalies, and provide actionable insights to development teams, ensuring faster feedback and higher software reliability.
Your Impact As a Python DevOps Engineer within the Quality Assurance team, you will architect and scale AI-driven validation solutions that automatically test and assess software work products across automotive programs. You’ll design Python-based frameworks, define automation architecture, and integrate advanced AI-powered verification connected to CI/CD pipelines.
Key Responsibilities
AI Test Architecture, Development & Integration
- Design, develop, and maintain AI automation for automotive projects.
- Create and maintain AI automation scalable solutions for automotive projects.
- Enable and optimize solutions with a focus on efficiency and execution time, ensuring high stability of results.
- Configure and operationalize remote execution environments, including authentication, cluster setup, and performance tuning.
- Integrate AI automation solutions into Jenkins and GitHub Actions CI/CD pipelines.
- Interact with PL team to bring fully compatible AI automation solutions aligned with CI/CD strategy.
Python Automation & Framework Development
- Build robust Python frameworks supporting build/test automation, data collection (PostgreSQL, SQL), orchestration, and continuous verification.
- Develop modular libraries, CLI tools and interfaces, internal APIs, and automation logic aligned with CI/CD standards.
Engineering Workflow Automation
- Automate integration flows across tools, microservices, internal systems, and external vendors.
- Improve developer experience by reducing execution time, optimizing caching strategies, and simplifying workflows.
Dashboards, Observability & Reporting
- Build dashboards to visualize AI Automation performance, CI/CD metrics, quality indicators, pipeline health, and operational KPIs.
- Develop data pipelines to collect, process, and surface telemetry across distributed systems.
Cross-Team Collaboration
- Work closely with global software teams, platform architects, and DevOps specialists to align and extend engineering capabilities.
- Promote best practices in Python, Bazel, CI/CD, Git workflows, and automation design principles.
Troubleshooting & Continuous Improvement
- Diagnose failures, pipeline bottlenecks, misconfigurations, caching issues, and integration conflicts.
- Continuously explore improvements such as parallel execution, rule optimization, pipeline refactoring, and new DevOps tools.
- Server configuration and maintenance.
Requirements
What We’re Looking For
Must-Have Skills
- Strong expertise in Python (framework design, automation, OOP, threads, CLI, API).
- Strong experience with Jenkins and/or GitHub Actions for CI/CD.
- Familiarity with Windows Server IIS.
- Solid understanding of Git, branching strategies, and workflow automation.
- Good grasp of CI/CD concepts and modern DevOps practices.
- Strong analytical, debugging, and problem-solving skills.
- Comfortable working in agile environments with shifting priorities.
- Good English communication skills.
Nice-to-Have Skills
- Experience with large-scale build systems or monorepos.
- Experience developing dashboards (Grafana, Kibana, or custom Python solutions).
- Familiarity with Linux, Bash scripting, containers, or microservices.
- Experience with migration projects (tools, pipelines, build systems).
- Background in automotive, embedded, or high-reliability software environments.
- Experience with Gen AI tools (Vero, Goose, …).
Your Mindset
- System-thinker who enjoys architecting engineering ecosystems.
- Driven by automation, optimization, and developer productivity.
- Thrives in complex environments with global stakeholders.
- Balances long-term technical vision with immediate business needs.