Senior Full-Stack Software Engineer, MeridianLink

• Ability to assess unusual circumstances and use sophisticated analytical and problem-solving techniques to identify the cause, particularly with AI integrations
• Ability to resolve and assess a wide range of AI-related issues in creative ways and suggest variations in approach
• Ability to devise AI-powered solutions based on limited information and precedent and adapts existing approaches to resolve complex technical issues
• Strong foundation in both RESTful API development in Python and modern frontend development (React, TypeScript, Vite)
• Solid understanding of cloud environments with experience deploying full-stack AI applications
• Experience with modern development tooling across the stack and proficiency with AI-assisted development tools (GitHub Copilot, Claude, etc.)
• Track record of taking AI-powered features end-to-end from high-level product concepts to production deployment
• Ability to enhance relationships and networks with senior internal/external partners who are not familiar with AI/ML subject matter, often requiring persuasion and technical expertise
• Bachelor's degree and 6-8 years of related experience or equivalent work experience, with demonstrated experience in full-stack development and AI integration
• If you’re a self-driven engineer who enjoys working across the entire technology stack and is passionate about building the next generation of AI-powered applications — we’d love to meet you

Desirable

• We are seeking a Senior Full-Stack Software Engineer to join our growing team focused on developing AI-powered experiences for our products using Python, React, and modern cloud technologies. You'll work closely with product, design, and fellow engineers to craft seamless AI-powered features that empower users to do their best work
• Work on AI-powered services that are used across product lines, developing both backend APIs and frontend interfaces
• Mentor lower-level peers and serve as an informal technical lead, particularly in AI/ML integration best practices
• Create and execute processes and procedures for the technical quality, security, performance, and consistency of AI-powered products
• Create "big picture" architectural approaches and implementation plans for AI-integrated software
• Ensure security, performance, and quality of software architectures and provide technical guidance to development teams
• Drive end-to-end system design decisions for scalable enterprise-grade AI platforms and collaborate with Product to evolve requirements into well-architected solutions
• Conduct research, gather information, interpret data, identify requirements, and create innovative solutions for AI-driven products
• Stay current on emerging AI/ML technologies, modern development tooling, and implement security best practices throughout the AI development lifecycle