Engineering Manager

Magna AI is a global AI company, purpose-build to deliver sovereign AI infrastructure, applications, and security for enterprise and governments worldwide.

We are looking for an R&D Lead to provide all three.

## About the Role

As R&D Lead, you will manage Magna's engineering team and own delivery for our products, working side by side with the Product Owner to turn the roadmap into shipped, production-quality releases.

You will also act as the team's AI subject matter expert. When the team faces decisions on model selection, fine-tuning, retrieval architecture, evaluation, or scaling, you are the person who sets direction and raises the technical bar.

This is a player-coach role for someone who has both led engineering teams and built machine learning systems at scale in production—not someone who has only managed from a distance.

You will operate in a fast-moving, multicultural environment, collaborating across teams, geographies, and time zones. An agile mindset, adaptability, and the ability to navigate different working styles and perspectives will be critical to success in this role.

## What You'll Do

* Lead, coach, and grow a team of AI, platform, and software engineers.

* Own end-to-end delivery for Magna's products, from planning through release and post-release quality.

* Partner closely with the Product Owner on roadmap, scoping, prioritization, and trade-off decisions.

* Act as the team's AI SME, setting technical direction on models, architectures, and evaluation.

* Guide decisions on model selection, fine-tuning, retrieval pipelines, and agentic system design.

* Establish the team's engineering practices, including code review, testing, CI/CD, and release discipline.

* Run the delivery cadence, including sprint planning, estimation, dependency management, and status reporting.

* Foster an agile way of working, continuously adapting processes and priorities as business and product needs evolve.

* Unblock the team technically, stepping into design reviews and hard problems when needed.

* Manage delivery risk, flag issues early, and keep stakeholders informed with clear and transparent status.

* Collaborate effectively across multicultural and geographically distributed teams, building alignment across different perspectives and ways of working.

* Hire, onboard, and develop engineers as the team scales.

* Ensure what ships is production-ready for regulated, sovereign enterprise environments.

## What We're Looking For

* Proven experience leading and managing engineering teams delivering production software.

* Strong hands-on background in AI and machine learning at scale.

* Deep familiarity with LLMs, retrieval-augmented generation, fine-tuning, and model evaluation.

* Track record of owning delivery, including planning, execution, and shipping on committed timelines.

* Experience working closely with product owners or product managers in an agile setup.

* *An agile and adaptable mindset*, with the ability to operate effectively in a fast-moving environment, adjust priorities, and navigate ambiguity while maintaining delivery momentum.

* *Strong cross-cultural collaboration skills*, with the ability to lead and influence effectively across diverse, multicultural, and geographically distributed teams and stakeholders.

* Strong software engineering fundamentals, including architecture, code quality, and system design.

* Ability to go deep technically while keeping the team, timeline, and stakeholders on track.

* Strong Python skills and comfort reviewing and contributing to production code.

* Experience with MLOps, model deployment, monitoring, and iteration in production.

* Clear communication with both engineers and executive stakeholders.

## Nice to Have

* Experience building or deploying agentic AI systems or LLM-based products.

* Experience in platform engineering, including infrastructure, model serving, or developer platforms.

* Exposure to security engineering or secure-by-design practices for enterprise systems.

* Experience in financial services, healthcare, government, telecom, or other regulated industries.

* Experience leading engineering teams across multiple countries, time zones, and organizational cultures.

* Background in sovereign, on-premise, or air-gapped AI deployments.

* Prior experience scaling an engineering team in an early-stage or high-growth environment.