We're looking for an AI Workflow Engineer to join our System Architecture group. This is a high-impact role where you'll design, build, and continuously improve AI-powered workflows, agents, and tools that help our architects do their best work - from system design and modeling through documentation, technical decision-making, and review.
Working from within the architecture team, you'll turn the group's real, day-to-day pain points into practical AI-assisted solutions. Your primary focus is system architecture within the software development lifecycle (SDLC), and because architecture touches everything, your work will naturally extend into adjacent stages wherever AI can add value.
Design and build AI-powered workflows, agents, and internal tools that support system architecture work — design, modeling, documentation, architecture decisions, and reviews.
Develop and iterate on agents within our internal framework, using agentic AI techniques to accelerate and augment architecture and engineering tasks.
Continuously improve existing workflows and tools as team needs evolve and AI capabilities advance.
Partner closely with the System Architecture team to understand real pain points and turn them into practical, AI-assisted solutions.
Requirements
B.Sc . or M.Sc. in Computer Science, Electrical Engineering, or a related field, graduated with Honors
AI Development Tools: Hands-on experience using AI-powered coding assistants and agentic development tools - not just familiarity, but meaningful integration into your workflow.
Communication: Ability to explain technical concepts clearly and influence adoption across teams with varying levels of AI experience.
Quality-driven mindset: You care about getting things right — reducing noise, improving accuracy, and measuring whether output is actually good. You iterate relentlessly and aren't satisfied with "good enough."
As part of the initial stages of the recruitment process, you will be required to submit an AI project presentation based on a project built using Claude Code.
Measure and demonstrate the impact of the workflows you build - for example on design-cycle time, review turnaround, and the quality and completeness of architecture documentation and decision records.
Build proof-of-concept projects that show the practical value of AI in real architecture and engineering workflows.
Develop best practices, prompt engineering guidelines, and reusable patterns for AI-assisted architecture and development.
Stay current with the rapidly evolving AI tooling landscape and advise on strategic adoption.