AI Data Analytics Engineer

Job Details

Job Location:

Fort Collins, CO 80528

Position Type:
Full Time Salary Range: $ - $ Salary

Travel Percentage :
Negligible Job Category:
Engineering

BillGO is building the next generation of payments. Our vision is to be the payment accelerator for Small Business: an intelligent network that helps businesses get paid faster, operate leaner, and grow with confidence.

• The design, build, and delivery of data models, analytics pipelines, and AI/ML features embedded in BillGO's payments products and internal tools.
• Warehouse and semantic-layer modeling, metrics definitions, and self-serve analytics that make trusted data accessible across the business.
• Integration of large language models, embeddings, and retrieval-augmented generation (RAG) systems that turn analytics data into intelligent experiences.
• Data pipelines, evaluation frameworks, and monitoring that keep analytics and AI features accurate, safe, and observable in production.
• Prompt engineering, model selection, and build-versus-buy tradeoffs balancing quality, latency, and cost.
• Responsible and secure use of data and AI appropriate for a regulated payments environment.
• Partnership with Application Engineering, Platform Engineering, and Data Platform & Intelligence to embed analytics and AI into existing services and APIs.

• 3-5 years of experience building and shipping production software or data products, with meaningful experience in analytics engineering and AI/ML feature development.
• Proficiency in Python and SQL, and experience with modern data and AI/ML tooling: data warehouses (e.g., Snowflake, Big Query, Redshift), transformation frameworks (e.g., dbt), LLM APIs, vector databases, embeddings, and orchestration frameworks such as Lang Chain, Lang Graph, or similar.
• Solid engineering fundamentals: data modeling, APIs, cloud platforms, CI/CD, testing, and observability.
• Understanding of BI and analytics tooling, semantic layers, prompt engineering, RAG, model evaluation, and guardrail or safety practices.
• Experience with data pipelines and both structured and unstructured data.
• Fintech, payments, or regulated-industry experience is a plus but not required.
• Strong collaboration and communication skills; comfortable working cross-functionally with product, platform, and data teams.