Lead Backend Engineer, AI Platform
Lead backend engineer building and scaling AI-powered platforms and service-oriented architectures. Responsibilities include designing LLM-integrated workflows, mentoring engineers, and managing cloud-based distributed systems using languages like Python, Go, or Java.
- Compensation
- $220K–$300K / yr
- Location
- Toronto, Canada
- Work setup
- Remote
- Seniority
- Lead
- Employment
- Not specified
- Experience
- 2+ years
- Category
- Backend
- Posted
Skills
Must have
- 5-8+ years of experience building and operating production-grade backend systems
- 2+ years of experience in a technical lead or engineering leadership capacity
- Experience with modern backend programming languages (Python, Go, C++, Rust, Java, etc.)
- Experience with API design and service-oriented architecture
- Experience deploying and operating services on major cloud platforms (AWS, GCP, or Azure)
- Experience building AI-enabled product capabilities on top of LLMs
- Strong SQL skills and application data modeling experience
Nice to have
- Experience in fintech, mortgage, lending, or other regulated domains
- Experience with event-driven platforms (Kafka, Kinesis, SQS/SNS, etc.)
- Experience with AI platform components (vector databases, retrieval pipelines, etc.)
- Experience building secure identity and access control systems
Full description
Overview
The Lead Backend Engineer on the AI Platform team plays a critical role in building, evolving, and leading the backend systems and engineering practices that power internal products, customer‑facing capabilities, AI‑enabled workflows, and operational decision‑making across the organization. This role combines hands‑on backend engineering depth with technical leadership, delivery ownership, and mentorship for engineers working on business‑critical systems.
This role contributes to the development and evolution of core backend capabilities, including service‑oriented architecture, APIs, workflow orchestration, event‑driven integrations, identity and permissions, and operational tooling. In addition, the Lead Backend Engineer will drive buildouts of AI application infrastructure, LLM‑powered product capabilities, agentic workflows, retrieval‑augmented systems, evaluation pipelines, and shared platform patterns. Success requires strong technical judgment, sound systems thinking, and the ability to guide a team toward simple, scalable, and maintainable solutions in a cloud‑based, regulated, high‑stakes environment.
The Lead Backend Engineer is expected to operate effectively in a modern engineering environment, using automation, observability, CI/CD, testing, infrastructure‑as‑code, and AI‑assisted development practices to deploy, manage, and improve backend systems. In parallel, this individual will help set technical direction, break down ambiguous problems, mentor engineers, raise the quality bar through design and code review, and partner closely with Product, AI, Data, Operations, and business stakeholders to build both with AI and on top of AI responsibly, securely, and pragmatically.
This is a fully remote position that offers a competitive salary range of $220,000 to $300,000 USD, plus an annual bonus. You'll also receive our excellent benefits package, which includes medical coverage starting on day one and a company‑matched 401(k). Compensation may vary based on experience, location, and other job‑related factors.
Responsibilities
Scale High‑Performance Distributed Systems
- Design, build, and maintain production backend services for a wide variety of internal and external use cases, including product workflows, operational tools, integrations, APIs, and AI‑enabled applications
- Develop well‑structured APIs, domain models, service interfaces, and business logic that are easy to understand, test, operate, and extend
- Build scalable backend workflows that support complex business processes across loans, documents, accounts, users, permissions, vendors, and operational decision making
- Remain hands‑on in critical areas of the codebase, especially where technical direction, architectural leverage, incident resolution, or execution speed requires senior engineering judgment