Staff Software Engineer Fullstack

What You'll Bring

Qualifications

• BS/MS in Computer Science or related field, or equivalent practical experience
• 7+ years of experience building and delivering enterprise-grade applications
• Solid understanding of algorithms, design patterns, and software architecture
• Strong experience developing applications using JavaScript and mid-tier languages like Java
• Proficiency in building scalable, accessible, and internationalized applications across web and mobile
• Experience developing and deploying applications in cloud environments
• Hands-on knowledge of microservices architecture, CI/CD pipelines, container technologies (e.g., Kubernetes, Docker, Mesos)
• Strong experience in SQL and NoSQL database design and performance optimization
• Background in test automation and TDD, including unit, integration, and functional testing

AI & Emerging Tech

• Practical experience integrating AI models into applications (e.g., LLM prompting, AutoML, embedding models)
• Skilled in evaluating and monitoring AI performance in production environments
• Ability to lead AI integration efforts while mentoring other engineers on leveraging AI
• Understanding of best practices for safely and efficiently using AI in production systems

Soft Skills

• Strong communicator with the ability to influence across engineering, product, and executive teams
• Experience collaborating with data scientists, AI researchers, product managers, and cross-functional peers
• Passion for mentoring, growing others, and sharing knowledge across teams

How You Will Lead

Responsibilities

• Drive significant, cross-cutting technology initiatives from design to production
• Architect and develop durable, scalable, and secure systems that interact with multiple platforms
• Collaborate across teams to design AI-integrated solutions that deliver high business impact
• Provide architectural guidance and coding best practices across application and platform development
• Continuously learn and apply cutting-edge technologies, sharing findings with the broader engineering organization
• Launch and monitor AI-driven features in production, using performance and user metrics to guide improvements
• Coach and mentor junior engineers on software engineering principles, AI adoption, and system design
• Actively foster a culture of innovation, technical excellence, and continuous improvement