AI Data Analytics Engineer – Payments Platform

BillGO; Fort Collins (CO); On-site; USD 102,000 - 146,900; Full time

Job summary

BillGO in Fort Collins, CO is seeking an analytics engineer to design and deliver data models, analytics pipelines, and AI/ML features embedded in our payments products and internal tools.

You will shape warehouse and semantic-layer modeling, define metrics, and enable self-serve analytics that make trusted data accessible across the business, while integrating LLMs, embeddings, and RAG systems for smarter experiences.

Qualifications

• 3–5 years of experience building production software or data products with analytics and AI features.
• Proficient in Python and SQL; experienced with data warehouses and AI tooling.
• Strong collaboration and cross-functional communication skills.

Responsibilities

• Design, build, and deliver data models, analytics pipelines, and AI/ML features.
• Model warehouses and semantic layers; enable self-serve analytics across the business.
• Integrate large language models, embeddings, and retrieval-augmented generation (RAG) systems into analytics.
• Develop data pipelines, evaluation frameworks, and monitoring to ensure accuracy and observability.
• Handle prompt engineering, model selection, and build-versus-buy tradeoffs.
• Ensure responsible and secure use of data and AI in a regulated payments environment.
• Collaborate with Application Engineering, Platform Engineering, and Data Platform & Intelligence teams to embed analytics and AI into services and APIs.

Skills

Python

SQL

Analytics engineering

AI/ML

Data modeling

Tools

Snowflake

BigQuery

Redshift

dbt

LangChain

LangGraph

vector databases

embeddings

LLM APIs

Job description

BillGO in Fort Collins, CO is seeking an analytics engineer to design and deliver data models, analytics pipelines, and AI/ML features embedded in our payments products and internal tools.

You will shape warehouse and semantic-layer modeling, define metrics, and enable self-serve analytics that make trusted data accessible across the business, while integrating LLMs, embeddings, and RAG systems for smarter experiences.