Principal Engineer; AI

The Principal Engineer (AI) is the highest-ranking individual contributor and a software engineer at heart, with deep expertise in artificial intelligence, including large language models, machine learning, generative AI, agentic systems, and related technologies. The role applies AI frameworks, principles, and best practices to influence the platform's technical vision, help the team leader guide delivery teams through complex AI and non-AI technical problems, and work closely with the VP of Software Development to drive innovation and long-term technical strategy.

With a primary focus on advancing AI/ML capabilities, this role defines and evolves the organization's approach to LLMs, ML platforms, GenAI applications and agentic systems. The Principal Engineer (AI) ensures that all technology initiatives, AI and non-AI, are technically robust, ethically responsible, and aligned with business outcomes while acting as both a hands‑on technical leader and strategic thought partner.

Resolver is now permanently hybrid – that means you can decide to work in office, remotely or a mix of both depending on your preference. That location you see above is the region you are able to work within.

• Define the north star for AI and related technologies and create the strategy that connects it to business success.
• Define and drive the technical vision and long‑term strategy for the platform, with a primary focus on AI/ML (LLMs, GenAI, agentic systems, MCP systems, ML platforms) while also contributing to non‑AI initiatives.
• Align technical goals with business objectives, ensuring the platform evolves to meet current and future needs.
• Communicate and advocate the technical vision effectively to both technical and non‑technical stakeholders, bridging strategy and execution.

• Ensure systems AI and non‑AI are designed and integrated in a way that is scalable, secure, and consistent with architectural best practices.
• Provide oversight and guidance on AI and non‑AI system architecture, ensuring coherence, scalability, performance and security.
• Review AI solution designs, data strategies, and model implementations for robustness, fairness, and compliance.
• Collaborate with other senior technical leaders to define and enforce architectural standards, patterns, and best practices.
• Lead critical architectural initiatives, including AI integration with existing systems and platforms.

• Be the go‑to expert who tackles the toughest technical challenges, designing robust solutions to critical AI and engineering problems.
• Perform in-depth analysis and root cause investigations for critical system and model issues.
• Design and implement innovative, resilient solutions to complex problems across AI and non‑AI domains.
• Serve as the escalation point for the most difficult technical challenges faced by engineering teams.

• Grow the organization's technical talent by mentoring engineers, promoting responsible AI practices, and fostering a culture of excellence and innovation.
• Inspire, mentor, and coach senior engineers, data scientists, and technical leaders to grow talent and capability.
• Promote a culture of excellence, continuous learning, responsible AI adoption, and innovation across the engineering organization.
• Lead by example – while providing guidance and support for professional development – demonstrating technical excellence, thought leadership, and ethical responsibility in AI practices.

• Bachelor’s degree or higher in Computer Science, Engineering, Data Science, or a related field, or equivalent practical experience.
• Demonstrated success in designing and delivering scalable, reliable, and high‑performing AI and software solutions within complex technical environments.
• Strong proficiency in modern software and AI architecture principles, including design patterns, distributed systems, MLOps practices, and emerging AI/ML technologies (LLMs, GenAI, vector databases, MCP, etc.).
• Master‑level proficiency in Python, with hands‑on experience in additional languages such as…