BillGO, Inc.
Job Details
Job Location : Fort Collins, CO 80528
Position Type : Full Time
Salary Range : $132,800.00 - $185,000.00
Travel Percentage : Negligible
Job Shift : Day
POSITION SUMMARY The Software Engineer designs and builds infrastructure and applications for BillGO’s products. This role will be collaborating internally with teammates and other teams as well as externally with third party vendors through a variety of transmission protocols. This role will be fully responsible for code through design, implementation, maintenance, and monitoring. The ideal candidate will have a strong background in Java development, Cloud architecture, and experience in the financial industry.
About the Role As our Issuing Engineer, you will:
Design, build, and maintain the core systems behind our virtual card issuing platform
Integrate AI-powered services for fraud detection, anomaly monitoring, and transaction insights
Build APIs and services that power card creation, spend controls, tokenization, and reconciliations
Collaborate with Product, Risk, and AI/ML teams to develop machine learning–driven authorization rules and customer-facing analytics
Work closely with network partners (Visa, Mastercard) and issuing processors to ensure secure, compliant, and performant issuing flows
Act as a subject matter expert on issuing technology and AI-driven enhancements
What You’ll Do
Lead technical development of issuing features: card lifecycle management, spend controls, tokenization, and real-time transaction processing
Own integrations with card networks and issuing processors (Marqeta, Galileo, Lithic, or direct to network)
Build resilient, observable systems that handle real-time authorization events and sensitive payment data
Implement real-time AI-based fraud detection pipelines that learn from transaction patterns
Integrate LLM-powered support and operations tooling for internal teams (e.g., automated dispute summaries, transaction anomaly explanations)
Build AI-driven customer dashboards showing spend patterns, merchant risk profiles, and cost optimization recommendations
Participate in architecture reviews, incident response, and production hardening
Monitor and optimize system performance and cost-efficiency as the platform scales
Stay current on card network updates, fraud trends, AI advancements, and regulatory shifts
Qualifications You May Be a Good Fit If You
Have 5+ years backend engineering experience, ideally in FinTech or Payments
Have 2+ years working directly on card issuing, processing, or payment systems
Are comfortable with card networks, BIN sponsors, issuing processors
Understand authorization flows, ISO8583, PCI-DSS, and tokenization
Are fluent in backend development (Node.js, Python, Go, or Java) and distributed system design
Have hands-on experience integrating AI/ML models into production systems
Can design secure, auditable, and highly-available services
Are product-minded and love influencing roadmaps with data-driven and AI-enabled insights
Thrive in startup environments with evolving needs
Nice to have
Experience with Marqeta, Galileo, Lithic, or other issuing platforms
Experience with fraud detection models, merchant categorization ML, or real-time anomaly detection
Familiar with vector databases and LLM orchestration frameworks (LangChain, Semantic Kernel, etc.)
Built customer-facing AI features such as transaction categorization, forecasting, or spend optimization
Exposure to PCI-DSS, SOC 2, KYC/AML, and compliance-heavy environments
What Success Looks Like in This Role
Modernize the issuing platform to support 3–5x transaction volume growth while improving authorization latency, resiliency, and operational visibility.
Reduce infrastructure and processing costs through architectural improvements, smarter routing, and data-driven performance optimization.
Improve partner onboarding velocity with card networks and processors by standardizing integrations and reducing custom operational overhead.
Deliver actionable insights via dashboards and analytics that help customers optimize spend, manage risk, and reduce costs.
Continuously adapt authorization logic using ML-driven insights from live transaction data, merchant behavior, and customer usage patterns.
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POSITION SUMMARY The Software Engineer designs and builds infrastructure and applications for BillGO’s products. This role will be collaborating internally with teammates and other teams as well as externally with third party vendors through a variety of transmission protocols. This role will be fully responsible for code through design, implementation, maintenance, and monitoring. The ideal candidate will have a strong background in Java development, Cloud architecture, and experience in the financial industry.
About the Role As our Issuing Engineer, you will:
Design, build, and maintain the core systems behind our virtual card issuing platform
Integrate AI-powered services for fraud detection, anomaly monitoring, and transaction insights
Build APIs and services that power card creation, spend controls, tokenization, and reconciliations
Collaborate with Product, Risk, and AI/ML teams to develop machine learning–driven authorization rules and customer-facing analytics
Work closely with network partners (Visa, Mastercard) and issuing processors to ensure secure, compliant, and performant issuing flows
Act as a subject matter expert on issuing technology and AI-driven enhancements
What You’ll Do
Lead technical development of issuing features: card lifecycle management, spend controls, tokenization, and real-time transaction processing
Own integrations with card networks and issuing processors (Marqeta, Galileo, Lithic, or direct to network)
Build resilient, observable systems that handle real-time authorization events and sensitive payment data
Implement real-time AI-based fraud detection pipelines that learn from transaction patterns
Integrate LLM-powered support and operations tooling for internal teams (e.g., automated dispute summaries, transaction anomaly explanations)
Build AI-driven customer dashboards showing spend patterns, merchant risk profiles, and cost optimization recommendations
Participate in architecture reviews, incident response, and production hardening
Monitor and optimize system performance and cost-efficiency as the platform scales
Stay current on card network updates, fraud trends, AI advancements, and regulatory shifts
Qualifications You May Be a Good Fit If You
Have 5+ years backend engineering experience, ideally in FinTech or Payments
Have 2+ years working directly on card issuing, processing, or payment systems
Are comfortable with card networks, BIN sponsors, issuing processors
Understand authorization flows, ISO8583, PCI-DSS, and tokenization
Are fluent in backend development (Node.js, Python, Go, or Java) and distributed system design
Have hands-on experience integrating AI/ML models into production systems
Can design secure, auditable, and highly-available services
Are product-minded and love influencing roadmaps with data-driven and AI-enabled insights
Thrive in startup environments with evolving needs
Nice to have
Experience with Marqeta, Galileo, Lithic, or other issuing platforms
Experience with fraud detection models, merchant categorization ML, or real-time anomaly detection
Familiar with vector databases and LLM orchestration frameworks (LangChain, Semantic Kernel, etc.)
Built customer-facing AI features such as transaction categorization, forecasting, or spend optimization
Exposure to PCI-DSS, SOC 2, KYC/AML, and compliance-heavy environments
What Success Looks Like in This Role
Modernize the issuing platform to support 3–5x transaction volume growth while improving authorization latency, resiliency, and operational visibility.
Reduce infrastructure and processing costs through architectural improvements, smarter routing, and data-driven performance optimization.
Improve partner onboarding velocity with card networks and processors by standardizing integrations and reducing custom operational overhead.
Deliver actionable insights via dashboards and analytics that help customers optimize spend, manage risk, and reduce costs.
Continuously adapt authorization logic using ML-driven insights from live transaction data, merchant behavior, and customer usage patterns.
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