Senior Software Engineer

Point Predictive; San Diego (CA); On-site; USD 150,000 - 170,000; Full time

Benefits offered by this job

401(k)

AD&D insurance

Dependent health insurance coverage

Flexible spending account

Health insurance

Life insurance

Paid holidays

Paid time off

Vision insurance

Job summary

Point Predictive is seeking a Senior Software Engineer to design, build, and maintain the production platforms behind core products, including real-time APIs, data ingestion, and decisioning systems.

You will work closely with engineering peers, Data Science, and Product to ensure models, data, and customer-facing systems are production-ready. The role emphasizes ownership, quality, and leveraging AI tools for velocity and reliability.

Qualifications

• 5–8+ years of software engineering experience building production systems.
• Proven ability to deliver reliable systems at scale with strong execution.
• Experience with distributed systems and full-stack development (APIs, backend, UI).
• Experience building and scaling systems in cloud environments (AWS preferred).
• Hands-on engineering approach with architecture, debugging, and critical decisions.
• Experience in high-growth or scaling environments, evolving systems through change.
• Experience with QA, release processes, and progressive deployment (shadow mode, canaries).
• Experience with monitoring, alerting, and observability across distributed systems.
• Experience partnering with data science teams to productionize machine learning models.
• Comfort using AI-assisted development tools to improve productivity and reduce errors.

Responsibilities

• Design, build, and maintain APIs and real-time decisioning systems, ensuring reliability and production outcomes.
• Contribute to front-end design and development to support web-based products.
• Improve release practices with automated testing, regression coverage, and safe deployments.
• Maintain high code quality and share knowledge via code reviews and guidance.
• Implement real-time monitoring, alerting, and observability across the stack.
• Contribute to architecture decisions for scalable, high-performance systems.
• Collaborate with Data Science to productionize ML models in real-time systems.
• Support live resolution of production issues and risk mitigation.
• Follow and help improve CI/CD, incident response, and operational excellence.
• Leverage AI-assisted tools to boost productivity and testing rigor.

Skills

Distributed systems

Full-stack development

API design

AWS

QA and release processes

Observability and monitoring

Production systems

Collaboration with data science

Education

Bachelor's or Master's

Tools

AWS

Job description

Point Predictive is redefining fraud detection and risk decisioning for lenders through large-scale consortium data, machine learning, and real-time systems. We are seeking a Senior Software Engineer to help design, build, and maintain the production platforms behind our core products, including real-time APIs, data ingestion, and decisioning systems that operate at scale across financial institutions.

In this role you'll work closely with engineering peers, Data Science, and Product to ensure that models, data, and customer-facing systems are seamlessly integrated and production-ready. The ideal candidate brings strong technical depth and execution rigor — a hands-on engineer who takes ownership of the systems they build, raises the bar on quality, and leverages modern AI tools to improve engineering velocity and reliability.

Responsibilities

• Design, build, and maintain APIs and real-time decisioning systems, taking ownership of the reliability and production outcomes of the components you work on
• Contribute to front-end design and development to support web-based products
• Support the QA team through improvements to release practices, including automated testing, regression coverage, and safe deployment techniques (e.g., shadow mode, canary releases)
• Set a high bar for code quality and accountability, and share knowledge with peers through code review and technical guidance
• Implement real-time monitoring, alerting, and observability across the stack to proactively detect and resolve issues before customer impact
• Contribute to architecture decisions across backend and frontend systems, ensuring scalability, performance, and a consistent user experience
• Bring a focus to maintaining and improving API response times.
• Partner closely with Data Science to productionize machine learning models in real-time systems
• Support live resolution of critical production issues
• Follow and help improve strong engineering practices across CI/CD, incident response, and operational excellence
• Leverage modern AI-assisted development tools (e.g., Claude Code) to improve your productivity, testing rigor, and overall engineering quality
• Collaborate with Product and Customer teams to smoothly configure and implement new customer integrations with Point Predictive products.
• Ensure the systems you build meet security, compliance, and data governance requirements in a regulated financial environment

Qualifications

• 5–8+ years of software engineering experience building and delivering production systems
• Proven ability to deliver reliable systems at scale and drive work to completion with strong execution
• Strong experience with distributed systems and full-stack development (APIs, backend, and UI)
• Experience building and scaling systems in cloud environments (AWS preferred)
• Hands-on engineering approach, with the ability to dig into architecture, debugging, and critical system decisions
• Experience in high-growth or scaling environments, building systems through change
• Solid experience with QA, release processes, and progressive deployment strategies (e.g., shadow mode, canary releases)
• Experience with monitoring, alerting, and observability across distributed systems
• Experience partnering with data science teams to productionize machine learning models
• Comfort leveraging AI-assisted / agentic development tools to improve engineering productivity and reduce errors
• Strong communication skills and the ability to collaborate effectively with cross-functional partners
• Experience in financial services, lending, or fraud detection is a plus

What Success Looks Like

• Consistent, reliable delivery of your work with minimal production issues
• Predictable, low-risk releases supported by strong testing and pre-production validation
• Issues identified and resolved proactively through monitoring and alerting
• APIs, UI, and decisioning systems that operate as a cohesive, high-performing platform
• Data science models seamlessly integrated into production
• AI tools applied to improve your speed and reduce errors
• Clear ownership, accountability, and strong cross-functional partnership

Why This Role

• Build and own meaningful parts of the engineering backbone of a company delivering real-time fraud and risk decisions
• High-impact role with direct, visible influence on product performance and customer outcomes
• Deep, hands-on technical work on real-time systems at scale during a critical growth phase
• Work closely with engineering and data science leaders to shape technical direction

Education

Bachelor\'s or Master\'s (Preferred)

Pay: $150,000.00 - $170,000.00 per year

• 401(k)
• AD&D insurance
• Dependent health insurance coverage
• Flexible spending account
• Health insurance
• Life insurance
• Paid holidays
• Paid time off
• Vision insurance

Application Question(s):

• This is an in-person role. Will you commute to the office every day?
• Our core values are 1) Be the Expert, 2) Get it Done, and 3) Pitch in. Describe in detail how you have embodied these values in the past and describe how you will continue to honor them in the future.