AI Engineer

Salary Range: $ To $ Annually

Location:

Centennial, CO (In-Office)
Company:
Yield Solutions Group

Reports to:

AI / Data Lead

Yield Solutions Group (dba Refi Jet) is one of the country's largest auto-refinance BPOs, processing more than 15,000 applications per month across a network of 30+ lending partners. We operate at the intersection of financial services, technology, and customer experience, and AI is central to how we plan to scale all three.

This role sits inside our Technology Department, which consolidates Product, Development, Dev Ops, AI/Data, IT, and Support under a single leadership structure. The AI Engineer reports directly to the AI / Data Lead and works across the full stack of AI development: data pipelines, model development, LLM tooling, and production deployment.

This is a production-focused role. You will own systems that run on real loan volume, influence real borrower outcomes, and operate under the SLA expectations of our lender partners. The work is high-visibility, the feedback loop is short, and the roadmap is yours to help shape.

The AI Engineer is responsible for designing, building, and maintaining AI-powered systems across the borrower journey, lender pipeline, and internal operations. Responsibilities span four domains.

• Partner with the CTO and product leadership to define the AI roadmap, prioritize use cases, and align engineering investment to business outcomes.
• Translate operational problems into well‑scoped ML and AI problem statements. Own the solution architecture from initial design through production deployment.
• Establish internal standards for AI development, including model evaluation frameworks, validation protocols, and responsible deployment practices.
• Present technical findings, tradeoffs, and recommendations clearly to non‑technical stakeholders, including operations leadership, lender partners, and executive teams.

• Build and deploy LLM‑powered tools, machine learning models, and automation pipelines that improve application processing speed, decisioning accuracy, and borrower experience.
• Design and implement data pipelines supporting model training, feature engineering, and real‑time inference at production scale.
• Run structured experiments, define success metrics before testing begins, and document outcomes regardless of result.
• Own model performance post‑launch. Build monitoring, alerting, and retraining workflows that keep systems reliable as data and conditions change.

• Identify underperforming AI systems and drive measurable, documented improvements.
• Evaluate new tools, frameworks, and model architectures against real business criteria. Distinguish signal from noise in a fast‑moving space.
• Collaborate with Dev Ops and Data teams to improve infrastructure for model serving, versioning, and CI/CD integration.
• Contribute to engineering culture through code reviews, internal documentation, and knowledge sharing across the Technology Department.

• Work with Compliance and Operations to ensure AI outputs meet Colorado regulatory requirements applicable to consumer lending and adverse action standards.
• Partner with lender integration teams to understand how AI‑driven outputs are consumed and acted on downstream.
• Support audit and explainability requirements for any model that influences credit‑adjacent workflows.
• Identify and elevate model risk proactively, including data dependency fragility, distributional drift, and edge‑case failure modes.

• 3+ years of professional experience building and deploying ML or AI systems in production environments.
• Strong Python proficiency with clean, maintainable, production‑grade code standards.
• Hands‑on experience with LLMs, including context engineering, fine‑tuning, retrieval‑augmented generation (RAG), agent harnesses, and LLM observability.
• Proficiency with ML tooling:
  PyTorch/Tensor Flow, or comparable libraries.
• Experience with cloud platforms (AWS, GCP, or Azure) and model deployment infrastructure.
• Solid data engineering fundamentals: SQL, ETL pipelines, feature engineering, and data validation.
• Demonstrated…