Location: Remote (U.S.)
Employment Type: Full-time
Department: Engineering
Why This Role MattersCardiff's edge is how quickly we can convert a lead into a funded customer. Today our average turnaround is 24 business hours; our goal is minutes, through automated systems with human-in-the-loop oversight. AI-native engineering has changed what one strong engineer can deliver, and we're staffing accordingly: not more headcount doing traditional work, but engineers who have rebuilt how they work around modern tooling and ship in days what used to take weeks. The work you do here goes straight into the systems that will get us there.
The RoleYou'll own vertical projects end to end: the customer-facing products and internal tools that sit on top of Cardiff's shared platform. You'll report directly to the Managing Partner, work with our Lead AI Architect on system design, and sit with the stakeholders behind each project (operations, sales, underwriting, marketing, finance) to turn what they need into working product, often inside a week. The team is small and senior. Your work will be in production your first week, and what you own will grow as fast as you show you can carry it.
What Success Looks LikeIn your first 90 days, you will:
- Ship a product to production that materially beats the status quo for the department you serve, measured on the KPI that fits: speed, accuracy, ROI, or conversions
- Take at least two more prototypes to production with clearly defined before-and-after KPIs
- Build positive working relationships with stakeholders
- Learn Cardiff's business model and integration surface well enough to ship against it without hand-holding
By the end of your first year:
- A portfolio of production systems you own, with attributable impact on funding volume, conversion, or operating cost
- Faster product cycles across the team, with AI-assisted development patterns you introduced now in common use
- A track record of judgment: systems that scale, and AI-generated code that got read, audited, and corrected rather than merged on faith
What You'll Do- Own each project end to end: backend, frontend, deployment, and iteration once it's live
- Design and launch AI agents that talk to customers, tied to results you can measure
- Work with the Lead AI Architect on architecture and the ongoing evolution of Cardiff's AI platform
- Build against our shared integrations: Salesforce, Snowflake, Gmail, Zoom, Slack, and internal tools
- Reach for best-in-class open source before building from scratch: where the work isn't core IP, adopting a strong community project (think Buzz, the agent-native workspace Block recently open-sourced) beats owning the support and upgrade burden of a homegrown clone
- Make AI tooling your default way of building, and read what it produces before it ships
- Ship a working v1 today and improve it Monday, instead of a "perfect" v1 a month from now
What We're Looking For- 5+ years of professional software engineering, with senior-level ownership of production systems
- Production features shipped using Claude Code, Cursor, Codex, Devin, or similar as your primary way of building, not occasional experimentation
- Own the testing for what you build, from unit through integration, and ensure it meets production-readiness standards before release.
- Finish things. Some of what you pick up will be sitting at 70 percent, and getting it to done counts more here than starting something new.
- A recent example (within the last six months) of using AI tooling to deliver something 3-5x faster than you could have without it
- Range across the stack: Python, modern JavaScript/TypeScript, SQL, REST/GraphQL, and cloud deployment (AWS preferred)
- Depth in agent orchestration (loops, graphs, multi-step tool use, multi-agent patterns; LangGraph or similar), with LLM APIs, RAG and vector databases, prompt engineering, and evals running in production, not just prototypes
- 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
- The engineering fundamentals to recognize when AI output is wrong
Nice to have:
- Salesforce APIs, Snowflake, or fintech/lending data models
- Contributions to open-source AI projects
- Experience shipping solo or on a small founding team
Who Does Well HereYou ship: a rough v1 in production beats a polished v1 in staging. You're fine with priorities that move. You work independently and communicate proactively; when something is blocked, you say so the same day.
You know the frontier better than we do. We're not looking to teach you the latest capabilities; we're looking to be wowed, and to learn from you.
We care less about the brand on your resume than what you've shipped in the last 90 days. A self-taught engineer with a GitHub full of working AI-native projects beats a 15-year veteran just starting to explore these tools. Show us the work.
This Role May Not Be a Fit If You- Prefer structured corporate environments with clear lanes
- Want detailed direction before you start
- Would rather maintain systems than build them
- Use AI tools to assist your old workflow, rather than having rebuilt your workflow around them
Compensation and Benefits- Base salary from $110,000, with room above it for the right person
- Performance bonus of up to 20% of base, tied to delivery and business outcomes
- Medical, dental, and vision coverage
- 401(k) plan
- Flexible PTO and observed holidays
- Remote-first, with support for your home-office setup
- Direct access to leadership and to the problems that matter
