Staff Backend Engineer (AI Platform team)

Quo•Canada, KY

2d•$185,000 - $242,000

About The Position

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.

Requirements

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.

Responsibilities

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.