Senior Applied AI Engineer (Enterprise AI / Python)

Role overview

• check_circle Design and implement scalable AI services and supporting infrastructure that enable AI-powered product capabilities across the platform
• check_circle Develop solutions for evaluating and improving LLM output quality
• check_circle Build frameworks and tooling that support AI feature development across the engineering team
• check_circle Develop and maintain systems that support model tuning, evaluation, and optimization
• check_circle Contribute directly to deployment and operational reliability of AI services in production environments
• check_circle Optimize AI services for latency, cost efficiency, and reliability
• check_circle Partner with the CTO to evaluate emerging AI capabilities and recommend technical approaches for model usage, architecture, and system design
• check_circle Provide technical guidance to engineers building AI-powered features and help establish effective development patterns and engineering best practices
• check_circle Contribute to technical architecture discussions related to AI systems and platform capabilities
• check_circle Contribute meaningfully to establishing reliable systems supporting AI-powered product features within your first 90 days
• check_circle Improve the performance, consistency, and reliability of AI-generated outputs
• check_circle Develop systems and frameworks that enable rapid experimentation while maintaining production-grade reliability and engineering quality
• check_circle Help establish development patterns and technical practices that enable other engineers to build AI-powered features more effectively
• check_circle Demonstrate strong technical leadership and ownership of AI system design and implementation
• check_circle 5+ years of software engineering experience, including strong backend or systems development experience
• check_circle Strong Python development experience
• check_circle Experience designing and building backend services or distributed systems
• check_circle Experience integrating LLM APIs, generative AI services, or AI-enabled capabilities into production systems
• check_circle Experience evaluating or improving AI model performance in production environments
• check_circle Strong problem-solving and systems design skills
• check_circle Ability to collaborate effectively in a cross-functional team

Preferred qualifications

• Experience with FastAPI or similar frameworks
• Experience with model fine-tuning, retrieval-augmented generation (RAG), prompt evaluation, or LLM evaluation methods
• Experience building internal tooling or infrastructure supporting AI applications
• Experience working with vector databases or AI data pipelines
• Experience working in fintech or B2B SaaS environments
• Build meaningful technology that helps people improve their financial lives
• Work on practical AI applications deployed in a live fintech product
• Collaborate in a remote-first environment with experienced product and engineering leaders
• Competitive compensation, benefits, and equity
• Annual performance bonus
• Equity participation
• Comprehensive benefits package

About the company