Lead Backend EngineerThe 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 $260,000 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.ResponsibilitiesDesign, 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 applicationsDevelop well-structured APIs, domain models, service interfaces, and business logic that are easy to understand, test, operate, and extendBuild scalable backend workflows that support complex business processes across loans, documents, accounts, users, permissions, vendors, and operational decision makingRemain hands-on in critical areas of the codebase, especially where technical direction, architectural leverage, incident resolution, or execution speed requires senior engineering judgmentLead the design of service architectures that support transactional, operational, analytical, and AI-driven workloads across production environmentsDefine practical patterns for service boundaries, idempotency, consistency, retries, failure handling, schema evolution, versioning, backward compatibility, and operational ownershipGuide technical design reviews, architecture discussions, and implementation plans to ensure systems are simple, secure, reliable, observable, and maintainableMake sound technical tradeoffs that balance speed, simplicity, reliability, security, cost, and long-term platform leverageLead the design and implementation of LLM-powered backend capabilities, including retrieval, tool use, workflow orchestration, structured outputs, human-in-the-loop review, evaluation, guardrails, and production monitoringEstablish patterns for integrating AI systems with core services, data stores, document workflows, permissions, audit trails, operational decisioning, and user-facing product experiencesUse AI-assisted development tools thoughtfully to accelerate software delivery while maintaining strong standards for code quality, testing, security, maintainability, and human ownership of technical decisionsPartner with AI, Data, Product, and Operations teams to translate model capabilities, business workflows, and user feedback into reliable product experiences that improve over timeLead, mentor, and develop backend engineers through technical guidance, design feedback, code review, pairing, coaching, and clear expectations for engineering qualityTranslate ambiguous business, product, and operational needs into clear technical plans, milestones, sequencing, risks, and execution paths for the teamCoordinate delivery across engineers and partner teams, helping remove blockers, manage dependencies, clarify ownership, and keep work moving with urgency and disciplineHelp create a strong team culture grounded in ownership, high standards, candid feedback, pragmatic decision-making, and continuous learningDeploy, operate, and improve backend services on major cloud platforms such as AWS, GCP, or AzureUse infrastructure-as-code, CI/CD, automated testing, and deployment automation to improve release speed, consistency, and reliabilityMonitor production services using logging, tracing, metrics, alerting, and observability tooling to proactively identify and resolve issuesSupport secure, resilient, cost-conscious, and well-documented operation of cloud-based backend infrastructure and application servicesBuild and lead systems with strong operational discipline, including attention to latency, availability, scalability, correctness, incident response, and production supportImplement and review authentication, authorization, permissions, audit logging, data protection, and secure service-to-service communication patternsEstablish and maintain standards for API documentation, service ownership, runbooks, operational metrics, change management, release readiness, and production supportContribute to practices that support security, privacy, auditability, compliance, and risk management in a regulated environmentPartner closely with Product, Engineering, Data, AI, Design, Operations, and business stakeholders to understand workflows, user needs, constraints, and delivery prioritiesTranslate business and operational requirements into clean, scalable, maintainable, and secure backend solutions, while helping stakeholders understand technical tradeoffs and delivery risksSupport downstream consumers of backend capabilities, including product teams, analysts, researchers, AI systems, operational users, and external integrationsCommunicate clearly with both technical and non-technical stakeholders about system behavior, tradeoffs, risks, dependencies, incidents, and delivery timelinesQualifications5-8+ years of experience building and operating production-grade backend systems, APIs, services, or distributed applications2+ years of experience operating in a technical lead, team lead, staff-level project lead, engineering manager, or equivalent engineering leadership capacityStrong software engineering fundamentals, including data structures, algorithms, system design, debugging, testing, code quality, and pragmatic architecture decision-makingExperience designing, building, maintaining, and debugging services that run in production and support real users or business-critical workflowsExperience with modern backend programming languages such as Python, Go, C++, Rust, Java, Kotlin, Scala, TypeScript, or C#Experience with API design, service boundaries, event-driven or asynchronous architectures, relational data stores, and non-relational data storesExperience building transactional systems where correctness, idempotency, consistency, reconciliation, and auditability matterExperience deploying and operating backend services on major cloud platforms such as AWS, GCP, or AzureExperience building AI-enabled product capabilities on top of LLMs, foundation models, retrieval systems, embedding and search infrastructure, agent or tool-calling patterns, workflow orchestration, structured outputs, and human-in-the-loop reviewExperience integrating AI capabilities with backend systems, permissions, audit trails, document workflows, data pipelines, APIs, operational decisioning, and business-critical user experiencesDemonstrated ability to use AI-assisted development tools to improve engineering velocity while maintaining code quality, security, review discipline, and accountability for technical decisionsStrong SQL skills and comfort with application data modeling, schema evolution, migrations, query performance, and data access patternsExperience leading technical design, breaking down ambiguous problems, sequencing work, managing dependencies, and helping engineers make high-quality implementation decisionsExperience mentoring engineers through design review, code review, debugging, production support, career development, and feedbackStrong judgment in ambiguous environments where requirements evolve and systems must balance speed, reliability, security, compliance, and flexibilityPreferred ExperienceExperience in fintech, mortgage, lending, payments, insurance, banking, capital markets, or other regulated domainsExperience with queues, streaming, and event-driven platforms such as