Principal Software Engineer, Pricing Platform

Upstart is an AI lending marketplace focused on reducing the cost and complexity of borrowing through technology. The Principal Software Engineer will provide cross-company technical leadership for the pricing platform, shaping its architecture and roadmap while leading scalable, low-latency, highly reliable services that convert machine-learning underwriting outputs into pricing decisions.

Responsibilities:

• Define the cross-company technical vision and roadmap for Upstart's pricing platform, ensuring alignment across Pricing, Personal Loans, Auto, HELOC, ML, and Product organizations
• Lead the architectural evolution from tightly coupled, sequential workflows toward modular, reusable platform capabilities across loan products
• Design and improve Tier 0/Tier 1 services where latency, throughput, availability, and financial correctness are all critical
• Partner closely with machine-learning scientists and engineers to create reliable, scalable boundaries between models and production pricing systems
• Balance the sometimes-competing needs of engineering, machine learning, and product teams across organizations, making pragmatic trade-offs that serve Upstart's broader technical and business strategy
• Clarify service, API, configuration, and ownership boundaries across Pricing, Personal Loans, Auto, HELOC, and adjacent platform teams
• Evaluate runtime and language choices pragmatically, including where Python, Kotlin, Rust or Go best serve long-term system needs
• Reduce operational burden through better testing, observability, failure isolation, incident learning, and architecture that limits blast radius
• Lead company-wide technical discussions, surface trade-offs clearly, and build alignment across Engineering, ML, Product, Data, Security, Compliance, and business partners
• Stay close to implementation through design reviews, prototypes, and critical code while mentoring senior technical leaders and making the people around you more successful
• Prioritize technical-debt and platform investments based on business value, risk reduction, and long-term return rather than technical elegance alone

Requirements:

• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field - or equivalent practical experience - plus 8 or more years of software engineering experience
• A track record of setting architecture and technical direction for large, complex distributed systems used across multiple teams or products
• Deep backend engineering experience and production proficiency in at least one of Python, Kotlin, or Java; willingness and ability to work effectively in a predominantly Python environment
• Experience designing or operating Tier 0/Tier 1 services with demanding latency, throughput, availability, and correctness requirements
• Strong understanding of APIs, service-oriented or modular architectures, containerization, cloud infrastructure (e.g., AWS), and maintainable software design
• Hands-on technical judgment: you can move from strategy and architecture into concrete designs, prototypes, debugging, and critical implementation decisions
• Strong communication skills and the ability to explain complex systems, constraints, and trade-offs to technical and nontechnical audiences
• Demonstrated success leading cross-organization technical decisions — balancing the needs of engineering, machine learning, and product teams — and influencing without direct authority
• Experience mentoring senior engineers and expanding the effectiveness and scope of other technical leaders
• Strong product and business judgment, including the ability to balance delivery, reliability, technical debt, risk, and long-term investment
• Experience building calculation-heavy, real-time decisioning, pricing, marketplace, risk, fraud, payments, trading, auction, or advertising systems
• Experience partnering with machine-learning teams or productionizing models at scale, including clear boundaries between modeling workflows and production services
• Experience modernizing a mature or tightly coupled platform through staged migration while continuing to deliver customer and business value
• Experience with AWS, Kubernetes, microservices, event-driven systems, and production observability
• Additional production experience with Rust or another performance-oriented language
• Background or applied exposure in statistics, mathematics, economics, econometrics, financial systems, or other quantitative domains
• Experience in a rapidly scaling or changing organization where architecture had to evolve alongside the business