Distinguished Software Engineer

Overview

As the Distinguished Engineer, you are the senior-most individual contributor in Technology, reporting directly to the Chief Technology Officer. You will set the multi-year technical strategy for the company, owning the target enterprise architecture and the architecture for running AI agents across it, while staying hands-on in the code and systems.

What you'll do

• Convene the principal and staff engineers who own each domain to define the end-state enterprise architecture across originations, servicing, marketplace, data, and AI, and publish it including rejected tradeoffs.
• Own the enterprise agent architecture spanning servicing and collections, the dealer side, originations, and internal engineering and back-office workflows, on one common foundation.
• Establish a governed way for agents to discover and call business capabilities, data, and tools, using the Model Context Protocol as the integration layer.
• Define an identity and authorization model treating agents as first-class actors with least-privilege entitlements, along with observability, evaluation, and cost controls.
• Set policy on what an agent may decide independently versus what stays with a person, and design an examiner-ready audit record of what each agent saw, recommended, and touched.
• Own the technical strategy for migrating transactional workloads to AWS and analytical workloads to Databricks, including what lifts and shifts, replatforms, or is re-architected, the steady-state cost, and resilience and recovery for the target state.
• Set the data platform architecture for change-data-capture-based ingestion, streaming where warranted, and a modern warehouse with no job-scheduling dependency.
• Architect real-time pricing and credit model serving and an experimentation platform supporting far more concurrent experiments than a conventional release process allows.
• Own the architecture and interfaces for a unified vehicle inventory, consumer search, and lead routing platform supporting more than one class of seller.
• Define the AI-native engineering golden path, including the analyzers and gates that enforce it, and the build-versus-buy bar for AI capability.
• Own the instrumentation, baseline, and remediation architecture to meet the standard that no page takes more than one second, and own peak-event headroom and tested degradation levers.
• Work toward a two-week requirement-to-production iteration bar and name what comes off the plan whenever direction changes.

What you'll need

• Bachelor's degree in Computer Science, Information Systems, or closely related field of study; or equivalent work experience.
• Minimum 10 years of software engineering experience or comparable depth of experience.
• A track record of setting and delivering multi-year technical strategy at enterprise scale, as an individual contributor rather than through a reporting line.
• Depth in distributed systems architecture, and in at least two of: agentic or LLM-based systems in production; large-scale cloud migration of transactional systems; modern data platform and lakehouse architecture; machine learning platform and model serving; high-traffic consumer or marketplace applications.
• Architecture ownership of agentic or LLM-based systems that reached production, including how tool and data access were governed, how the system was evaluated, and what its failure modes turned out to be.
• Demonstrated ownership of a legacy-to-modern migration of systems the business runs on, including sequencing, cost case, and failure modes, with production revenue at stake.
• Hands-on credibility today: actively reads code, writes proofs of concept, joins design reviews, and participates in incident analysis.
• Evidence of influence without authority across organizational boundaries, including work that changed direction at the executive level.
• Strong written communication.
• Demonstrated ability to develop staff and principal engineers and raise the technical bar of engineers not directly managed.
• Experience delivering in a regulated industry, or a clear ability to work inside audit, security, and compliance constraints.

Nice to have

• Recognized contribution beyond one employer, such as open source, standards work, publications, patents, or a sustained external technical presence.
• Consumer lending, auto finance, insurance, or payments experience; or large-scale distributed systems experience supporting a business-critical function in another high-stakes domain.
• The Model Context Protocol or comparable agent tool-integration standards, and identity and authorization design for non-human actors.
• AWS and Databricks at production scale.
• Experience standing up an experimentation platform, or moving an organization from tens to thousands of experiments per year.
• Experience building AI-native development practice across a large engineering organization, and measuring whether it worked.
• Marketplace, search, or inventory systems with more than one class of seller.

Details

• Location: USA, remote.
• Target base salary range $232,500 - $341,000, eligible for equity and annual cash bonuses; premium may apply for candidates in San Francisco, Seattle, Boston, New York City, Los Angeles and San Diego.
• Employment type and work hours are not specified in the posting.