Cardiff

Own end-to-end vertical projects including backend, frontend, deployment, and AI agent design and launch. | 5+ years professional software engineering with production AI tooling experience, deep agent orchestration and modern web stack expertise, and rapid iteration in senior small teams. | Location: Remote (U.S.) Employment Type: Full-time Department: Engineering Why This Role Matters Cardiff'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 Role You'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 Like In 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 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 Here You 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 Benefits 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 How to Apply Email AI-Eng@cardiff.co with: A 2–3 minute video introducing yourself and walking us through your work A link to your GitHub A specific project you've shipped to production, with a link we can see or try Cardiff, Inc. is an Equal Opportunity Employer. We are committed to creating a diverse and inclusive workplace and do not discriminate on the basis of race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity, or any other characteristic protected by applicable law.

Design and maintain FastAPI services and AWS pipelines integrating financial data with LLM-assisted workflows ensuring data quality and compliance. | Requires 5+ years Python backend experience with FastAPI, Snowflake, AWS, and financial API integration. | Location: Remote (U.S. preferred), with East Coast hours overlap Employment Type: Contractor (ongoing), with a path to full-time employment Department: Engineering About Cardiff Cardiff lends to small businesses. Since 2004 we've funded more than $12 billion across the country, to businesses in logistics, healthcare, construction, professional services, and plenty in between. We're building our own underwriting technology, and we still answer the phone; our customers need capital fast, and they want a straight answer from a person who can actually help. Why This Role Matters Cardiff's underwriting decisions are only as good as the data behind them. This role owns that layer: the integrations that pull credit and bank transaction data from providers like Experian and Plaid, and the Python services that deliver it to the systems driving risk decisions. We're pushing funding turnaround from 24 business hours toward minutes, and that only works if the data underneath is fast, reliable, and compliant. As we expand ML-based decisioning and LLM-based workflows, this layer sets the pace for everything built on top of it. The Role This is a Python backend engineering role focused on financial data integration. You'll build and maintain the FastAPI services that deliver financial and credit data to Cardiff's internal systems, along with the provider integrations and AWS pipelines that feed them. You'll work as an individual contributor on Cardiff's technology team, alongside the Lead AI Architect and engineers covering full-stack, UI, and operations, with access to our AI platform from day one and real ownership over how you get the work done. The role starts as an ongoing contract with a clear path to full-time; we begin with a contract so both sides can evaluate fit through real work, and your scope will grow as you show you can carry more. What Success Looks Like In your first 90 days, you will: Ship at least one production integration with a financial or credit data provider (Experian, Plaid, or a bank transaction source) end to end Implement automated validation and quality checks across the pipelines you own, so failures surface before they reach downstream consumers Ship or materially extend a FastAPI service that exposes provider data internally, with tests and documentation another engineer can pick up cold Deliver a documented data model and schema mapping for at least one provider domain, built alongside our domain experts and analysts Demonstrate one LLM-assisted extraction workflow on unstructured input (bank statements, credit memos), with output validation in place By the end of your first year: The financial data layer is Cardiff's system of record: accurate, current, and complete enough that underwriting, risk, and operations decide on it with confidence Adding or replacing a data provider is a well-worn path rather than a project; the business can move on partnerships without waiting on engineering Compliance is a property of how the systems are built, not a scramble ahead of each review What You'll Do Design, build, and run the FastAPI services that expose financial and credit data to internal consumers: API design, auth, versioning, pagination, and clear error handling Own the integration layer with external providers (Experian, Plaid, bank transaction sources): retries, backoff, rate limiting, credential handling, and graceful degradation when a provider slows down or goes dark Build the pipelines that land provider data in Cardiff's systems, including Snowflake, using serverless ETL on AWS (Glue, Athena, Step Functions, S3 data lakes), supporting both batch and near-real-time ingestion Do the data modeling and schema mapping that keeps disparate provider formats semantically consistent, working with our domain experts and analysts Build integrations that meet Cardiff's security, privacy, and regulatory obligations, with Legal, Compliance, and Security owning final interpretation and sign-off Apply LLM APIs for extraction and classification of unstructured documents where it earns its keep, with model outputs validated before they enter the pipeline Make AI tooling part of how you build, and read what it produces before it ships Maintain the unit tests, integration tests, and documentation for every component you own What We're Looking For 5+ years of Python backend engineering on data-intensive systems, with the emphasis on recent, demonstrable work Production backend services built and operated in a modern Python framework (FastAPI preferred; Flask or Django fine), including API design, auth, testing, and async programming Reliable third-party API integration (retries, idempotency, rate limits, partial failures, observability), ideally against financial APIs from credit bureaus, banks, or payment processors Substantial hands-on Snowflake experience in production: loading, modeling, and large-scale querying AWS data services for pipeline orchestration (Glue, Athena, S3, Step Functions, Lambda), including data lake layouts and partitioning that keep querying cost-efficient Strong data modeling, schema alignment, and transformation instincts A working grasp of API authentication, encryption, and the compliance requirements that come with regulated financial data Proficiency in SQL and Pandas Nice to have: Credit decisioning, loan underwriting, or financial risk data experience LLM APIs (Claude, OpenAI, or equivalent) applied to extraction, classification, or summarization, plus the applied-LLM toolkit: prompt design, evals, output validation, RAG and embeddings AI-assisted development tools (Claude Code, Cursor, Codex, Devin) as a primary mode of building CI/CD pipelines Who Does Well Here You ship: a working v1 today beats a polished v1 next month. You sweat data correctness, because bad data that looks fine is the most expensive failure in a lending business. You treat AI tooling as a force multiplier, and you know when to trust the output and when to override it. You work independently and communicate proactively; when something is blocked, you say so the same day. 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 Benefits Medical, dental, and vision coverage 401(k) plan Flexible PTO and observed holidays Remote-first, with support for your home-office setup How to Apply After submitting your resume, email AI-Eng@cardiff.co with: A 2–3 minute video introducing yourself and walking us through your work A link to your GitHub A production project you've shipped, with a link we can see or try Cardiff, Inc. is an Equal Opportunity Employer. We are committed to creating a diverse and inclusive workplace and do not discriminate on the basis of race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity, or any other characteristic protected by applicable law.