AI Engineer

Location: Centennial, CO (In-Office)
Company: Yield Solutions Group
Reports to: AI / Data Lead

The Opportunity

This role sits inside our Technology Department, which consolidates Product, Development, DevOps, 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.

What You'll Do

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.

Strategy & Leadership

• 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.

Discovery & Execution

• 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.

Growth & Optimization

• 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 DevOps 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.

Partnership & Compliance

• 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 escalate model risk proactively, including data dependency fragility, distributional drift, and edge-case failure modes.

Required Skills & Experience

• 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/TensorFlow, 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 ability to evaluate model performance rigorously, with working knowledge of bias/variance tradeoff, drift, and distributional shift.
• Clear written and verbal communication, including the ability to explain model behavior and failure modes to non-technical audiences.

Nice to Have

• Experience with auto lending, auto refinancing, or consumer credit products.
• Familiarity with loan origination systems (LOS), credit decisioning, or lending infrastructure.
• Expertise with creating custom skills, plugins, slash commands, hooks, or MCP servers to encode team workflows and standards.
• Technical fluency with APIs, integrations, or platform-based products.
• Experience working with external partners or B2B clients in a product-led organization.

Compensation & Benefits

Base Salary: $130,000 - $160,000 annually, commensurate with experience

Bonus: Performance-based incentives tied to company and individual goals

Benefits: Comprehensive benefits including health, dental, vision, life insurance, 401(k), PTO, career development opportunities, and the chance to join Denver's Best Place to Work (2024 and 2025) with a dynamic culture focused on internal promotion and employee growth.