AI Developer, Digital Enterprise
Confirmed on the employer's own hiring board on Oct 17, 2026. First seen by Alion on Aug 21, 2026. Magna scores B on the Alion truth index.
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What we offer:
At Magna, you can expect an engaging and dynamic environment where you can help to develop industry-leading automotive technologies. We invest in our employees, providing them with the support and resources they need to succeed. As a member of our global team, you can expect exciting, varied responsibilities as well as a wide range of development prospects. Because we believe that your career path should be as unique as you are.
Group Summary:
Magna is more than one of the world’s largest suppliers in the automotive space. We are a mobility technology company built to innovate, with a global, entrepreneurial-mindedteam. With 65+ years of expertise, our ecosystem of interconnected products combined with our complete vehicle expertise uniquely positions us to advance mobility in an expanded transportation landscape.
Job Responsibilities:
We are seeking a highly skilled AI Developer to join our team and drive the design, implementation, and scaling of advanced AI solutions. This role combines in-depth coding expertise with a strong systems engineering mindset: you’ll own the execution of end-to-end AI platform lifecycle-from infrastructure, and MLOps pipelines to production deployment and ongoing performance optimization. You’ll collaborate closely with solutions architects, data scientists, DevOps engineers, and product owners to turn models into reliable, secure, and maintainable services at enterprise scale.
Major Responsibilities
Design, build, and maintain AI/ML platform components (training clusters, feature stores, inference services, GenAI, vision, RAG, NLP).
Develop and manage infrastructure-as-code for scalable deployments (Terraform, ARM template)
Implement and operate CI/CD pipelines for automated model training, testing, and deployment
Integrate AI services with existing systems via APIs, messaging, and data pipelines
Monitor performance, reliability, and model drift; establish alerting and incident-response runbooks.
Optimize system performance through capacity planning, performance tuning, and disaster-recovery strategies
Write, and maintain high-quality, reusable code and libraries (C#, Python, Java)
Collaborate with cross-functional teams (Architect, Data Science, DevOps, Security) and document system designs and SOPs.
Knowledge and Education
Bachelor’s or Master’s degree in Computer Science, Electrical/Computer Engineering, or related field
Work Experience
3+ years in software engineering roles, with 2+ years building and operating AI/ML platforms
Proven track record delivering production-grade AI services at scale
Skills and Competencies Required to Perform the Job
Cloud Platforms: Proficiency with various cloud platform services for compute, storage, and networking (e.g. AWS, Azure etc.)
Containerization & Orchestration: Hands-on experience with Docker, Kubernetes, Helm
Strong skills and knowledge in distributed system architecture, integration, software design patterns, and object-oriented programming concepts and patterns. (Microservices, Monolith, Modular Monolith, containerized applications, etc.)
MLOps: Building and managing pipelines using GitLab CI, Argo CD, MLflow
Programming Languages: Advanced Python (including async and multithreading); familiarity with C#, Python, or Java.
LLM Application & Agent Frameworks: Experience designing and implementing RAG/agentic workflows using LangChain and LangGraph (tooling, chaining, memory, orchestration)
Machine Learning Frameworks: Deep knowledge of TensorFlow, PyTorch, scikit-learn
Data Engineering: Experience with Kafka, Azure Data Factory, Databricks, and Beam for data ingestion and processing
Monitoring & Observability: Implementing observability stacks (Azure Monitor, Prometheus, Grafana, ELK) and alerting
Security & Compliance: Securing data pipelines, understanding of GDPR/CCPA implications
Cross-Functional Collaboration: Effectively partner with Data Science, DevOps, Security, and Product teams
Technical Documentation: Clear authoring of runbooks, SOPs, and API specs
Stakeholder Communication: Translating technical concepts into business terms for executives and non-technical audiences
Presentation Skills: Leading demos, technical deep dives, and knowledge-sharing sessions
Continuous Learning: Staying current with emerging AI/ML, MLOps, and platform engineering trends
Working Conditions and Environment
No Travel
Any Additional Information
Excellent English in both spoken and written.
Excellent problem-solving and decision-making abilities.
Strong communication skills and the ability to lead cross-functional teams.
Awareness, Unity, Empowerment:
At Magna, we believe that a diverse workforce is critical to our success. That’s why we are proud to be an equal opportunity employer. We hire on the basis of experience and qualifications, and in consideration of job requirements, regardless of, in particular, color, ancestry, religion, gender, origin, sexual orientation, age, citizenship, marital status, disability or gender identity. Magna takes the privacy of your personal information seriously. We discourage you from sending applications via email or traditional mail to comply with GDPR requirements and your local Data Privacy Law.
AI-Assisted Screening Disclosure
As part of our commitment to a fair, consistent, and efficient recruitment process, we may use artificial intelligence (AI) tools to assist in the initial screening of applications submitted through our Workday system. These tools help identify qualifications and experience that align with the role requirements. Please note that AI is used solely to support our recruiters. Final decisions are always made by the hiring manager and the hiring team. Importantly, no applicant data is shared externally through these AI tools. All information remains securely within our systems and is handled in accordance with our privacy and data protection policies.
Under conditions defined by applicable law, you may have the right to request an explanation of how AI is used to support decision-making.
If you have any questions or concerns about this process, feel free to contact our Talent Attraction team.