AI Engineer II

Role overview This AI Engineer II position sits within a software engineering team dedicated to embedding artificial intelligence into a SaaS product. The role focuses on designing, implementing, and maintaining machine learning and deep learning models that solve real business problems inside a multi-tiered software platform. It combines hands-on data science work with traditional software engineering practices, contributing to the intelligent capabilities of a bill payment and receivables automation suite.

Responsibilities

- Design and build non-traditional data models for predictive modeling and complex representation or interpretation challenges. - Apply statistical and mathematical techniques to perform exploratory data analysis and validate proposed solution approaches. - Use existing machine learning libraries and frameworks to accelerate development, while staying current with advances in the AI field. - Extend traditional application architectures with intelligent systems design, owning model lifecycle quality and guiding improvements. - Debug, optimize, and refactor code to ensure performance, security, and scalability, following documented standards and best practices. - Collaborate with product owners, QA automation engineers, DBAs, architects, and scrum teammates to translate business needs into shipped features, and mentor junior engineers.

Requirements

- Bachelor's degree in Computer Science, Computer Engineering, or a related field with 5+ years of software development experience, or a Master's degree with 3+ years of experience on multi-tiered systems. - Strong working knowledge of C#, R, and Python. - Demonstrated experience with statistical learning methods and core AI concepts and system design. - Solid grasp of sound coding practices including unit testing, object-oriented programming, design patterns, and SOLID principles. - Proficiency with version control systems such as Git in continuous integration environments, and hands-on experience with Agile processes like Scrum or Kanban. - Familiarity with secure coding practices, including awareness of the OWASP Top Ten.

Nice to have

- Exposure to Hadoop, Spark, or Databricks, as well as .NET data tooling like Deedle, F# Data Toolbox, or XPlot. - Experience extending traditional application models through AI sub-disciplines such as computer vision, natural language understanding, autonomous or robotic systems, machine learning, deep learning, or reinforcement learning. - Background in systems engineering, feedback control systems, or model-based software engineering.

Benefits and work setup

- Hybrid workplace flexibility with free on-site parking and amenities such as a gym, yoga studio, and basketball court. - 18 days of PTO, 16 hours of paid volunteer time off annually, and 11 holidays. - Multiple health plan options including a high-deductible plan with $0 monthly premium for teammate-only coverage, plus 100% employer-paid dental, life, and both short- and long-term disability insurance. - Employee Assistance Program, on-site health clinic, parental leave, childcare support, and a discount program for personal purchases. - 401(k) with employer matching, and tuition reimbursement up to the federal annual maximum.