About the Job

As Splitero's Applied AI Engineer, you will own the identification, scoping, and delivery of AI-powered capabilities across our product and operations. You'll sit within the engineering organization but operate cross-functionally, partnering with product, operations, and business teams to identify where AI creates real leverage, then build it. Splitero sits at the intersection of financial services and property technology, and our product and engineering teams are at the center of that innovation every day. In this role, you'll work directly with our sales, processing, underwriting, closing, and servicing teams to identify, scope, and execute opportunities to streamline and automate their workflows as we scale. On the engineering side, you'll champion AI-first development, educate the team on emerging tooling, and lead technical initiatives that drive the organization forward.

You'll spend your time shipping working AI solutions into production by automating workflows, augmenting our product experience, and helping Splitero move faster and smarter as a business. You will have a strong understanding of when supervised AI outweighs the risk of full automation. You're as comfortable standing up a low-code n8n automation as you are writing clean code, and you know when each approach is the right one.

At Splitero, we move fast, and the ideal candidate thrives in that environment. You default to the simplest path to a working solution, prototype quickly using every tool available to you, and have the engineering discipline to know when something needs to be rebuilt properly before it goes to production.

Responsibilities:

AI Discovery & Strategy

Socialize AI capabilities, limitations, and roadmap across the org, acting as an internal resource and thought leader on what's possible.
Maintain a prioritized backlog of AI opportunities across the business, triaging ideas from leadership, product, and operations into scoped, deliverable workstreams.
Define AI initiatives end-to-end: problem framing, data requirements, build vs. buy decisions, and measurable success criteria.
Stay current on the AI tooling landscape and recommend adoption where it meaningfully improves velocity, quality, or competitive positioning.

Building & Delivery

Build, integrate, and maintain AI-powered features and workflows, leveraging LLM APIs (OpenAI, Anthropic, etc.), RAG pipelines, and agentic frameworks.
Develop automation workflows using low/no-code orchestration tools (n8n, Make) to deliver AI solutions rapidly without requiring full engineering cycles.
Integrate AI capabilities into existing systems and codebases in close partnership with the product and engineering teams.
Own the full AI development lifecycle, including prototyping, evaluation, deployment, monitoring, and iteration, with support from engineering, product, and operational teams.

Cross-Functional Partnership

Partner with product to translate user problems into AI-driven features and experiences.
Embed within operations and business teams to identify workflow automation and efficiency opportunities.
Collaborate with engineering to ensure AI integrations meet production standards for reliability, maintainability, and security.
Document and communicate AI implementations clearly so the broader team can support and build on them.

Reporting Structure

Reports directly to the VP of Product and Engineering
Embedded within the product engineering team, works cross-functionally across Salesforce, product, operations, and business functions

The salary range for this position is $135,000 - $175,000. Within the range, individual pay is determined by job-related skills, experience, and relevant education or training.

About You

6+ years in software engineering with at least 2 years of focused experience building production AI or LLM-powered applications
Hands-on experience with LLM APIs, prompt engineering, retrieval-augmented generation (RAG), and agentic workflow design. You are on the bleeding edge of the latest releases and advancements in AI platforms.
Demonstrated experience evaluating, advocating, and operationalizing AI tooling across an organization
Proficiency with low/no-code orchestration platforms (n8n, Make, Zapier) to prototype and deliver AI workflows rapidly
Comfortable with AI-assisted development tools (Claude Code, Cursor, GitHub Copilot, etc.) to accelerate build cycles, with the judgment to write clean, maintainable code when it matters. You are not a vibe code

Applied AI Engineer at Splitero