Sr GenAI Developer, Digital Enterprise

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What we offer:

Group Summary:

The Sr GenAI Developer is a full-stack developer who will act as the technical visionary and hands-on leader, responsible for designing, building, and delivering comprehensive GenAI software solutions that create business value. You will work closely with stakeholders—product managers, data scientists, solutions architects, UX/UI designers, and operations teams—to convert strategic goals into scalable architectures, utilizing both generative and traditional AI models alongside robust front-end and back-end systems. Your primary responsibilities include defining system requirements and roadmaps, leading development across cloud-native microservices and user-facing applications, ensuring code quality and performance, and implementing best practices in security, observability, and CI/CD. In this role, you will also mentor engineering teams, promote emerging AI capabilities, and continuously improve solution patterns to boost innovation and sustain our competitive advantage.

Major Responsibilities

• Define and document end-to-end solution architectures for GenAI services and full-stack applications, including high-level diagrams, data flows, and technology stack decisions

• Architect and manage scalable GenAI solutions using Azure services (e.g., AI Foundry, Apps Function, Storage Account, Cosmos DB, Azure AI search, Azure AI Services, AKS, VMs, Container Registry, etc.).

• Collaborate with product management and business stakeholders to refine requirements, prioritize features, and ensure alignment with strategic goals

• Lead design and implementation of microservices, APIs, and user interfaces, leveraging cloud-native platforms (e.g., Azure or AWS) and container orchestration (e.g., Kubernetes, Docker)

• Select, evaluate, and integrate generative AI models—fine-tuning, testing, and optimizing for production performance and cost efficiency.

• Establish and enforce engineering best practices around code quality, automated testing, CI/CD pipelines, and infrastructure-as-code (e.g., Terraform, ARM templates)

• Implement robust security, observability, and governance patterns, including identity management, data encryption, logging, and monitoring

• Mentor and coach development teams on architectural patterns, coding standards, and GenAI models deployment techniques.

• Drive proof-of-concepts and pilot projects to validate new technologies, tools, and frameworks, then translate learnings into reusable solution patterns.

• Evangelize GenAI capabilities across the organization—conduct technical workshops, brown-bags, and architecture reviews to build internal expertise.

• Ensure best practices in security, monitoring, and compliance within the cloud infrastructure.

• Continuously assess emerging trends in GenAI, full-stack development, and cloud infrastructure to recommend enhancements and maintain a competitive technology roadmap

Knowledge and Education               

• Bachelor’s degree in computer science, Software Engineering, Electrical Engineering, or a closely related technical field

• Master’s degree in Artificial Intelligence, Machine Learning, Data Science, or equivalent (preferred)

Work Experience

• Minimum of 6+ years of hands-on software development and architecture design

• At least 3 years leading end-to-end GenAI solution delivery in production environments

• 4+ years of full-stack application architecture, with proven expertise in cloud-native microservices.

Skills and Competencies Required to Perform the Job

• Proven experience with LLMs and NLP frameworks (e.g., Hugging Face, OpenAI, or Anthropic models).

• Implement LLMOps practices to streamline model deployment and CI/CD workflows.

• Cloud-Native Architecture: Experience designing scalable microservices and serverless solutions on Azure or AWS (e.g., Kubernetes, Docker)

• Full-Stack Development: Experience in hands-on coding in .Net, Python, or Java/Kotlin, and JavaScript/TypeScript with frameworks like React, Angular, and Node.js

• GenAI Expertise: Experience in selecting, fine-tuning, deploying, monitoring, and optimizing ML and generative AI models in production

• Data Engineering: Experience in building robust ETL/ELT pipelines, working with SQL/NoSQL stores and real-time streams (e.g., Kafka, Azure Event-Hub)

• Infra-as-Code & CI/CD: Experience in automating provisioning (e.g., Terraform, ARM template) and delivery pipelines (e.g., Jenkins, GitHub Actions) with automated testing

• Security & Observability: Experience in implementing IAM, encryption, secrets management, and logging/tracing/metrics (e.g., Azure Monitor, Prometheus, Grafana, ELK)

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.

• Passion for mentoring and developing engineers.

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.