About Arteria  Arteria AI is an award-winning, AI-powered documentation platform that transforms documents into data, facilitating critical banking processes like trading and lending. Leading banks worldwide use Arteria to connect costly, manual documentation processes to enterprise automation, providing valuable insights to decision-makers.  Founded in October 2020, Arteria completed its Series B funding round led by Notable Capital (formerly GGV Capital) in October 2023. Other investors include Citi, Illuminate Financial, Information Venture Partners, and BDC Capital. Arteria has received recognition from Gartner (“Cool Vendor” in AI for Banking), CB Insights (Global Top 100 Most Promising FinTechs, 2024, and Global Top 100 Most Promising AI Startups, 2023), and Finovate (Finovate Awards Winner), among others.  Arteria is headquartered in Toronto, with operations in New York and London.  About the Role  We are looking for an Engineering Manager to lead a small team building product features at the core of the Arteria platform. The near-term roadmap is meaty and clearly defined: rebuilding a new version of our document discovery surfaces, moving to a more modern document editor, and weaving AI features into both. This is a high-leverage role: the team’s output will shape what customers see and feel every day on Arteria.  The ideal candidate is a product-focused, technically credible engineering leader who is energised by working on hard problems with senior peers, develops the people on their team, and is not afraid of the difficult calls that come with running a high-performing team. You will partner closely with the Engineering Leadership, Product, Design, and AI Research to set technical direction and ship.  Key Responsibilities  Team Leadership & Development  * Lead, coach, and develop a team of 5–6 engineers, leveraging individual strengths to ship great product on a predictable cadence.  * Own the team’s talent bar end-to-end: hiring, onboarding, growth conversations, levelling, and ongoing development plans.  * Identify high-potential engineers early and create the conditions for them to grow into senior, staff, and lead roles over time.  * Make timely, fair performance-management decisions when they are required — including the harder conversations — and follow through with care and consistency.  * Set a tone of high standards, low ego, and clear feedback inside the team.    Technical Direction & Architecture  * Guide good technical decision-making across the team, steering it toward the right designs, trade-offs, and sequencing.  * Stay close enough to the code to be a credible technical partner; hands-on contribution is welcome where it adds leverage, but the primary value is direction, not individual output.  * Partner with the Engineering Leadership team, and other senior leaders to simplify the platform’s architecture and pay down complexity where it is slowing the team down.  * Raise the engineering standard on the team through code review culture, design reviews, on-call practices, and a thoughtful approach to tech debt.    Product Delivery  * Partner with Product and Design on the rebuild of our document discovery surfaces, the move to a more modern document editor, and the AI features we are weaving into both.  * Translate roadmap priorities into a clear plan of work, with realistic timelines, well-scoped milestones, and honest communication of risk.  * Drive predictable execution: keep the team focused, unblock issues quickly, and protect the team from churn so they can do their best work.  * Own quality outcomes for what your team ships — reliability, performance, and the experience of using the product.    AI & Engineering Productivity  * Stay curious about how AI tools can augment developer productivity on the team, building on the experimentation Arteria has already started.  * Champion adoption of effective AI-assisted workflows; coach the team on where these tools help and where they don’t.  * Share what is working with peers across engineering and contribute to Arteria-wide practices for AI in the development lifecycle.    Cross-functional Partnership  * Work closely with Product and Design to keep the team aligned on user problems and the why behind the work.  * Partner with AI Research and the broader Engineering org on shared platform, data, and AI capabilities.  * Engage with Customer Success and Professional Services on real-world feedback from financial institution clients, and bring that signal back into prioritisation.    Qualifications  * 7+ years of professional software engineering experience, including 2+ years managing engineering teams; experience leading a team of 5–10 engineers is ideal.  * A product-focused mindset: motivated by building software that solves real problems for users, not just shipping features.  * Strong technical judgment, with the credibility to guide architecture and design decisions in a modern web / SaaS environment; hands-on coding ability is a plus.  * Demonstrated interest in architecture and a track record of simplifying systems rather than just adding to them.  * Proven people-leadership skills, including hiring, coaching, levelling, and managing performance — comfortable making and communicating the harder calls when needed.  * Genuine curiosity about how AI is changing how software is built, and a desire to keep pushing on how the team uses AI tooling day to day.  * Experience in an early-stage, fast-growing environment where structure is being built rather than inherited.  * Experience working in or with financial institutions, fintech, or other regulated industries is an asset.    Compensation and Benefits  * For this role, candidates located in Ontario can expect a base salary range of CAD $150,000-200,000. Placement within the range is determined by relevant experience, skills, and role level. * In addition to base salary, this role is eligible for an end-of-year performance bonus and a comprehensive benefits package including health and dental coverage. * Comprehensive medical and dental insurance coverage, hybrid working environment, flexible time-off.    Arteria uses artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist the recruitment process but do not replace human judgment. Final hiring decisions are ultimately made by humans.