Senior Applied AI Engineer (Enterprise AI / Python)

About BrightPlan

BrightPlan is a leader in Total Financial Wellness. We provide a comprehensive global solution that addresses all aspects of employees’ financial health at every stage of life, empowering HR teams to enhance the employee experience and better attract, retain, and engage talent.

We are a remote-first SaaS company building practical AI-powered solutions that improve real financial outcomes for users. Our team values accountability, curiosity, thoughtful execution, and continuous learning.

We are expanding our engineering team to build the next generation of AI-powered financial wellness tools. This role focuses on building and shipping practical AI capabilities within a production SaaS platform rather than on research-oriented model development.

The Role

We are looking for a Senior Applied AI Engineer to help design, build, and scale the systems that power AI across the BrightPlan platform. This role will play an important part in shaping the evolution of AI systems within BrightPlan’s product architecture.

This role focuses on developing reliable, scalable infrastructure and frameworks for LLM-powered applications, enabling the broader engineering team to deliver reliable, high-quality AI features. You will work closely with the CTO to help shape technical decisions around AI architecture, model usage, and system evolution.

This role is ideal for an engineer who enjoys owning complex technical problems and building the systems that make production AI reliable and scalable.

This is an opportunity to have significant technical impact in a real-world fintech environment.

What You’ll Do

• Design and implement scalable AI services and supporting infrastructure that enable AI-powered product capabilities across the platform
• Develop solutions for evaluating and improving LLM output quality
• Build frameworks and tooling that support AI feature development across the engineering team
• Develop and maintain systems that support model tuning, evaluation, and optimization
• Contribute directly to deployment and operational reliability of AI services in production environments
• Optimize AI services for latency, cost efficiency, and reliability
• Partner with the CTO to evaluate emerging AI capabilities and recommend technical approaches for model usage, architecture, and system design
• Provide technical guidance to engineers building AI-powered features and help establish effective development patterns and engineering best practices
• Contribute to technical architecture discussions related to AI systems and platform capabilities

What Success Looks Like

• Contribute meaningfully to establishing reliable systems supporting AI-powered product features within your first 90 days
• Improve the performance, consistency, and reliability of AI-generated outputs
• Develop systems and frameworks that enable rapid experimentation while maintaining production-grade reliability and engineering quality
• Help establish development patterns and technical practices that enable other engineers to build AI-powered features more effectively
• Demonstrate strong technical leadership and ownership of AI system design and implementation