Senior Director of Software Engineering

Point Predictive; San Diego (CA); On-site; USD 180,000 - 195,000; Full time

Benefits offered by this job

401(k)

Flexible spending account

Health insurance

Health savings account

Life insurance

Paid time off

Vision insurance

Job summary

Point Predictive is seeking a Senior Director of Software Engineering to lead design, delivery, and reliability of our production platforms, including real-time APIs, data ingestion, and decisioning systems that scale across financial institutions.

The leader will partner with the VP of Data & Technology to align engineering with data science and product priorities, ensuring production-ready models, data, and customer-facing systems while scaling teams in a high-growth environment with

Qualifications

• 10–15+ years of software engineering experience with 5+ years in leadership roles
• Proven ability to deliver reliable production systems at scale
• Experience with distributed systems across APIs, backend, and UI
• Cloud environments experience, AWS preferred
• Hands-on leadership style with architecture and debugging skills
• Experience in high-growth environments and scaling teams
• Strong QA, release processes, and progressive deployment knowledge
• Experience partnering with data science teams to productionize ML models
• Comfort leveraging AI-assisted tools to improve productivity and quality
• Strong cross-functional communication and stakeholder alignment

Responsibilities

• Own engineering delivery and production outcomes across APIs, UI, and real-time decisioning systems
• Establish QA and release strategy with automated testing and canary/shadow deployments
• Implement monitoring, alerting, and observability across the stack
• Drive scalable architecture across backend and frontend systems
• Collaborate with Data Science to productionize ML models in real-time
• Lead and scale the engineering team and establish strong engineering practices
• Partner with Product and Customer teams for smooth deployments and integrations
• Own technical roadmap aligned to company priorities
• Ensure security, compliance, and data governance in a regulated financial environment

Skills

Distributed systems

Full-stack architecture

Cloud platforms (AWS)

Leadership and people management

QA & release management

Observability and monitoring

AI-assisted tooling

Cross-functional collaboration

Education

Bachelor's or Master's (Preferred)

Tools

AWS

CI/CD pipelines

Claude Code / AI-assisted development tools

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 Director of Software Engineering to lead the design, delivery, and reliability of our production platforms. This role will own the end-to-end engineering execution behind our core products, including real-time APIs, data ingestion, and decisioning systems that operate at scale across financial institutions.

This leader will partner closely with the VP of Data & Technology to align engineering with data science and product priorities, ensuring that models, data, and customer-facing systems are seamlessly integrated and production-ready. The ideal candidate brings a strong balance of technical depth, execution rigor, and leadership - with the ability to scale both systems and teams in a high-growth environment, while leveraging modern AI tools to improve engineering velocity and quality.

Responsibilities

• Own engineering delivery, system reliability, and production outcomes across APIs, UI, and real-time decisioning systems
• Establish and own QA and release strategy, including automated testing, regression coverage, and safe deployment practices (e.g., shadow mode, canary releases)
• Implement real-time monitoring, alerting, and observability across the full stack to proactively detect and resolve issues before customer impact
• Drive architecture across backend and frontend systems, ensuring scalability, performance, and a consistent user experience
• Partner closely with Data Science to productionize machine learning models in real-time systems
• Operate as a hands‑on leader, able to dive into system design, debugging, and critical production issues
• Lead and scale the engineering team, setting a high bar for execution, code quality, and accountability
• Establish strong engineering practices across CI/CD, incident response, and operational excellence
• Leverage modern AI‑assisted development tools (e.g., Claude Code) to improve productivity, testing rigor, and overall engineering quality
• Collaborate with Product and Customer teams to ensure smooth deployments and high‑quality integrations
• Own technical roadmap and execution aligned to company priorities
• Ensure systems meet security, compliance, and data governance requirements in a regulated financial environment

Qualifications

• 10–15+ years of software engineering experience, with 5+ years leading teams and managers
• Proven ability to drive engineering execution and deliver reliable production systems at scale
• Strong experience with distributed systems and full‑stack architecture (APIs, backend, and UI)
• Experience building and scaling systems in cloud environments (AWS preferred)
• Hands‑on leadership style, with the ability to engage in architecture, debugging, and critical system decisions
• Experience in high‑growth or scaling environments, with a track record of building teams and systems through change
• Strong 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 ability to align cross‑functional stakeholders
• Experience in financial services, lending, or fraud detection is a plus

What Success Looks Like

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

Why This Role

• Own and scale the engineering backbone of a company delivering real‑time fraud and risk decisions
• High visibility role with direct impact on product performance and customer outcomes
• Opportunity to build and shape a strong engineering organization during a critical growth phase
• Work directly with executive leadership to define technical direction and execution strategy

Education:

• Bachelor's or Master’s (Preferred)

Pay: $180,000.00 - $195,000.00 per year

• 401(k)
• Flexible spending account
• Health insurance
• Health savings account
• Life insurance
• Paid time off
• Vision insurance

Application Question(s):

• This is an in‑person‑only position. Will you commute to the office every day?
• Our Core Values are 1) Be the Export 2) Get it Done and 3) Pitch In. - Describe in detail how you have embodied these Values in the Past and how will you continue to honor them in the future.