AI Principal Engineer

So, what are the main responsibilities of the AI Principal Engineer in Netcompany’s Enterprise Solutions?

Joining us as an AI Principal Engineer, you will lead the design, delivery, and scaling of advanced GenAI, LLM, and Machine Learning (ML) solutions for enterprise clients across both public and private sectors. In this role, you will operate at the intersection of technical leadership, people management, and client engagement, driving impactful AI initiatives from concept to production.

You will act as a trusted advisor to senior client stakeholders, translating complex AI capabilities into clear business value, while leading and mentoring a high-performing team of AI/ML engineers. As a Principal (Manager-level role), you will be accountable not only for technical excellence but also for team growth, delivery quality, and client success.

This is a highly client-facing leadership role. Your ability to navigate complex stakeholder landscapes, align business and technology priorities, and communicate effectively with both technical teams and executive leadership will be key to success. You will represent the AI function in strategic discussions, lead workshops, and shape enterprise AI adoption roadmaps.

You will focus on the architecture and delivery of scalable, production-grade AI systems, ensuring solutions are reusable, extensible, and aligned with best practices, while pushing the boundaries of innovation beyond off-the-shelf tools.

As the AI Principal Engineer, you will:

• Serve as the primary AI and ML advisor to enterprise clients, translating business challenges into scalable AI-driven solutions with measurable impact.
• Lead, mentor, and grow a team of AI/ML engineers, fostering a culture of technical excellence, innovation, and continuous learning.
• Drive the end-to-end architecture and delivery of ML and GenAI pipelines, from ideation and prototyping to production deployment.
• Collaborate closely with MLOps, DevOps, and data engineering teams to ensure robust, scalable, and maintainable solutions.
• Manage stakeholder relationships across multiple projects, including executive communication, reporting, and risk management.
• Lead client workshops, discovery sessions, and technical presentations to define AI strategies and accelerate adoption.
• Oversee delivery quality, ensuring solutions meet performance, scalability, security, and governance standards.
• Contribute to practice development, including methodology, tooling, reusable assets, and pre-sales activities.