Staff Backend Engineer (Canada/North America)

Staff Backend EngineerLocation: Fully Remote; Pacific time-zone candidates prioritized About Coffee Meets BagelCoffee Meets Bagel is a women-founded company with a mission to give everyone a chance at love. We build products that help people form meaningful connections and work closely across Engineering, Product, Design, and Data to solve meaningful customer and business problems. We are modernizing both our product and engineering organization, investing in next-generation recommendation systems and GenAI capabilities and using AI-first development practices across the software lifecycle. The RoleWe are looking for a Staff Backend Engineer to be a technical leader for the systems that power Coffee Meets Bagel. You will play a key role in modernizing our backend architecture and building the foundation for the next generation of CMB's recommendation systems and AI-powered product capabilities. You will evolve APIs, distributed services, data flows, and system boundaries to support richer behavioral signals, modern ML systems, and future GenAI experiences. This role starts with deep backend expertise but extends beyond traditional backend boundaries. You will collaborate closely with mobile, infrastructure, data, and ML engineers and help shape both technical direction and product solutions. What You'll DoLead the architecture and evolution of backend services, APIs, distributed systems, and data-intensive workflows powering CMB's consumer product.Modernize backend systems to support next-generation recommendation systems, richer ML signals, and GenAI-powered product capabilities.Partner across mobile, infrastructure, data, and ML to define scalable system boundaries, interfaces, and integration patterns.Lead technical discovery for ambiguous, high-impact problems and make pragmatic tradeoffs across customer value, business impact, delivery speed, reliability, scalability, cost, and maintainability.Participate early in product discovery with Product, Design, Data, and Engineering—helping identify important problems, challenge assumptions, evaluate alternatives, and shape solutions rather than simply implementing predefined requirements.Raise engineering quality through sound architecture, code and design review, testing, observability, documentation, production readiness, and incremental modernization of legacy systems.Mentor engineers and use AI-assisted development across design, implementation, testing, debugging, review, and documentation while maintaining human accountability for technical judgment and production outcomes. What We're Looking ForDeep backend engineering experience with a strong track record designing, shipping, and operating complex production systems.Strong fundamentals in APIs, distributed systems, data modeling, databases, scalability, reliability, performance, and failure handling.Demonstrated Staff-level technical leadership: ability to turn ambiguous business, product, and technical problems into clear technical direction and drive significant initiatives through production.Strong architectural judgment and the ability to balance near-term product needs with sustainable technical investments.Strong product sense: you look beyond delivering a requested solution, seek to understand the customer and business problem, and identify opportunities where technology can create greater impact.Ability to influence and mentor engineers across teams, communicate clearly, work beyond a narrow specialization when needed, and adapt quickly as technologies and AI-assisted engineering practices evolve. Nice to HaveExperience in one or more of the following areas is particularly valuable: MLOps: productionizing models, inference systems, feature/data pipelines, model deployment, monitoring, experimentation, or evaluation.ML modeling: Hands-on experience developing ML models, or strong knowledge of modeling concepts such as feature engineering, training, evaluation, embeddings, deep learning, or model tradeoffs.Applied GenAI: building production features using foundation models, RAG, agents, multimodal models, embeddings/vector retrieval, or AI evaluation and guardrails.Experience building consumer, mobile, marketplace, or recommendation-driven products at meaningful scale. Our Technology StackOur environment includes Python, Go, PostgreSQL, Redis, Elasticsearch, vector databases, AWS, Docker, Kubernetes, queues and streams, CI/CD, automated testing, and observability tooling. You do not need prior experience with every technology in our stack. Strong engineering fundamentals, architectural judgment, and the ability to learn quickly matter more. How We WorkAt CMB, Engineering is not just a delivery function. Engineers participate in product discovery, understand customer and business problems, propose solutions, and share ownership of outcomes with Product and Design. We operate with an AI-first engineering culture, using AI throughout design, implementation, review, testing, debugging, and documentation while keeping engineers accountable for correctness, quality, security, and production outcomes. We also value depth plus breadth. Engineers bring deep expertise in an area such as backend engineering, while expanding over time across infrastructure, data, recommendation systems, ML, and applied AI as the problems and their impact require. To apply:Please submit your resume here on LinkedIn or email it to jobs@coffeemeetsbagel.com!