Director of Engineering

Cardiff

14d•$180,000•Remote

About The Position

This is the senior technology role at Cardiff, and it is a hands-on job rather than a strategy seat. You will run the engineering department day to day, carry the delivery dates yourself, and build alongside the team when that's the fastest way to unblock them. You own Cardiff's engineering department: the in-house engineering team, our outside contractors and offshore Salesforce developers, and the vendor relationships our roadmap depends on. You report to the Managing Partner and sit on the leadership team alongside operations, sales, underwriting, marketing, and finance; those departments are your internal customers. You'll set the delivery cadence, decide what gets built and what gets bought, keep production healthy, and be the single person the business goes to for a straight answer on status. The team is small and senior. Expect roughly 60% leading (planning, prioritization, review, unblocking, hiring) and 40% building; the ratio shifts toward building when we're behind. Cross-department program management runs in parallel to you rather than under you, and underwriting decisioning is owned by a dedicated hire who works directly with the Underwriting department. You'll partner with both; you won't be carrying their calendars.

Requirements

8+ years building production software, with 3+ years managing engineers directly; you've run a team of 4 or more
A track record of hitting dates on projects you owned, and a clear story about a date you missed and what you did about it
Still technical: you've written and shipped production code in the last year, and you can read a pull request and catch what's wrong with it
Agent systems in production, not prototypes: orchestration loops, graphs, multi-step tool use, multi-agent patterns, RAG over real data, and evals you actually run
Coding agents as your primary way of building; Claude Code, Cursor, Codex, or similar, with a recent example of delivering something 3–5x faster than you could have without them
Range across the stack: Python, modern JavaScript/TypeScript, SQL, REST/GraphQL, and cloud deployment (AWS preferred)
Build-vs-adopt judgment: fluent enough in the open-source AI ecosystem to reach for a strong community project rather than hand-rolling what already exists
Communication discipline: you escalate early in writing, and your stakeholders always know where things stand

Nice To Haves

Knowledge graphs, entity resolution, or unified data layers built for machine consumption
Fintech, lending, payments, or another regulated data environment
Salesforce APIs, Snowflake, or replacing a CRM-as-application architecture
Contributions to open-source AI projects
Experience as the most senior technical person in a small company

Responsibilities

Delivery: Every committed date in the department, including the ones you inherit
The team: Hiring, onboarding, one-on-ones, performance, and growth for in-house engineers and contractors; you'll inherit an open Senior Full-Stack Engineer (AI-Native) req and run that search
The platform: Our Salesforce/Fundingo core, the Cardiff API, Snowflake, cloud infrastructure, and the migration path off legacy systems
AI products in production: Customer-facing agents for collections, renewals, and win-back campaigns, plus internal agents that take work off people's plates
The knowledge layer: The graph and the pipelines that feed it, and the standard that new systems connect to it
Vendors: Technical evaluation, integration ownership, and honest reporting on whether a vendor is earning its invoice
Production quality and security: Uptime, data integrity, access control, and the incident response when something breaks
Run planning and prioritization with the department heads, and say no when the answer is no
Give proactive status: the business hears about slipped dates from you, on the day you know, not from asking
Design and operate agent systems: orchestration loops, multi-step tool use, retrieval against the graph, evals, and the human checkpoints that make them safe to run on customers
Review code and architecture, and stay close enough to production to know when an AI-generated pull request is wrong
Manage the offshore and contract developers to the same standard as the in-house team
Build against our stack: Salesforce, Snowflake, Gmail, Zoom, Slack, Twilio, and internal tools
Make AI tooling the department's default way of building, and hold the line on reading what it produces before it ships
Ship a working v1 today and improve it Monday, instead of a "perfect" v1 a month from now
Own the incident when something breaks in production, including the write-up afterward