AI Data Analytics Engineer

BillGO

Fort Collins (CO)

On-site

USD 102,000 - 146,900

Full time

14 days+

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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

Job DetailsJob Location: Fort Collins, CO 80528Position Type: Full TimeSalary Range: $102,000.00 - $146,900.00 SalaryTravel Percentage: NegligibleJob Category: EngineeringBillGO 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.

What you will own:
  • 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.
Qualifications
  • 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, BigQuery, Redshift), transformation frameworks (e.g., dbt), LLM APIs, vector databases, embeddings, and orchestration frameworks such as LangChain, LangGraph, 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.
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