Staff Backend Engineer (AI Platform Team)

Small businesses represent 99.9% of all companies, yet they're still forced to choose between clunky, outdated enterprise phone systems or their personal phones. This multi-billion dollar market has been overlooked for decades, left to cobble together solutions that slow them down instead of helping them grow. Quo is changing that. We bring calls, texts, and customer information together into one easy-to-use, AI-powered platform. We’re not just building a phone system. We’re setting a new standard for how businesses connect with their customers. Driven by our values, we move fast, build with determination, and obsess over delivering value to the businesses that have been underserved for far too long. Today, Quo is trusted by more than 90,000 companies and rated #1 in customer satisfaction on G2 . We’re backed by Y Combinator, Tiger Global, Craft Ventures, Slow Ventures, and other top-tier investors. It’s safe to say we’re onto something big. About the role OpenPhone’s AI capabilities power everything from intelligent call assistants to automated workflows that help thousands of businesses communicate better. As a Staff Backend Engineer, you will own the technical strategy for how we design, build, and operate AI features across the product. You’ll partner closely with leaders across engineering, product, and security to translate ambitious product ideas into scalable, dependable systems. Your architectural choices will shape how every customer experiences AI inside OpenPhone—from the very first trial call to fully deployed agents—and you’ll be trusted to balance cutting-edge innovation with rock-solid reliability. Some of the things you’ll do: Own the long-term architecture for AI orchestration frameworks, agent-based workflows, and model lifecycle management. Lead cross-functional delivery of AI features from proof of concept to production rollout, coordinating engineering, product, design, and CX. Establish best practices for prompt engineering, evaluation, versioning, observability, and incident response for AI services. Design and optimize low-latency streaming pipelines for speech and other real-time data when the customer experience demands it. Drive continuous cost, performance, reliability, and security improvements for models and infrastructure. Mentor engineers through design reviews, code reviews, and technical coaching, raising the bar for excellence across teams. Partner with security and platform leaders to ensure data privacy, compliance, and operational excellence. Stay current on advances in LLMs, agent architectures, and emerging tooling, translating insights into actionable roadmap proposals. Tech Stack & Tools: Our backend is built on Node using Typescript. Our AI Infrastructure uses temporal.io , vector DBs, libraries like Langchain and top-tier llm models. We use Kubernetes on AWS to orchestrate our infrastructure setup and deployment. The overall architecture is event-driven microservices with RabbitMQ at the center of it. We use a variety of databases for different purposes: Postgres, Mongo, Elastic, and Redis. We have the following clients - Web (React), Android and iOS. We use Kong as our public API Gateway. Observability Tools: Datadog Other Tools: Figma, Linear, Notion, and Slack About you 10+ years of backend or platform engineering experience, including LLM-driven systems in production. Proven success leading architecture for business-critical services, balancing innovation with operational pragmatism. Deep knowledge of LLM integration patterns, prompt design, vector search, and agent frameworks. Expertise in event-driven and streaming architectures; you can reason about concurrency, ordering, and back-pressure under load. Track record of driving cost optimization, observability, and incident response for AI workloads. Excellent written and verbal communicator who aligns diverse stakeholders and produces clear, thorough design docs. Collaborative leader who mentors others, fosters psychological safety, and elevates the entire engineering organization. Comfortable with ambiguity, you break down complex problems, make informed trade-offs, and deliver iterative value quickly. Empathetic and customer-focused, you balance technical decisions with user experience and business impact. Compensation The annual base salary range for this position is as follow, plus equity and benefits: SF Bay Area, Los Angeles, Seattle, Portland, Boston, New York, and Washington, DC Metro: $205,000-$242,000 USD All other US Locations: $185,000-$217,800 USD Canada: $189,000- $222,000 CAD The ranges displayed reflect the target for new hire salaries, and within each range, individual pay is determined by your skills and experience, as well as relevant education. Your recruiter can share more and answer questions about the specific salary range during the hiring process. Salary is just one component of Quo’s total compensation package. Your total rewards package will include equity, extensive medical coverage, a monthly lifestyle stipend, and a flexible PTO policy. Who we are As a fully remote company, we thrive as a team. We are curious, ambitious, and dedicated to our work. We value trust above all else, and have a strong bias for action. If you're looking for a place to do your life's work, please get in touch. We'd love to hear from you. And remember, there's no such thing as a 'perfect' candidate. We're looking for optimists with grit and determination, who are excited to face the challenges of a growing startup. Quo is the type of company where you can grow, and we encourage you to apply for this role even if you don't think you meet all the requirements. We are committed to creating an inclusive and diverse work environment. It is important that you are able to bring your authentic self to work every day. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. #LI-Remote #PostLI