AI Solutions Engineer

About the Role

The People Tech & Analytics team is responsible for building and owning the data, AI, and technology infrastructure for Affirm's People function. The team operates like a product engineering group embedded in HR, owning the full stack from data ingestion to production applications deployed on Snowflake. As a member of this team, you will have the opportunity to work on a wide range of projects, from building AI agents and APIs to deploying and maintaining production applications.

The success of the People Tech & Analytics team is critical to Affirm's mission to make credit more honest and friendly. By building and deploying AI-powered systems, you will be helping to drive business growth, improve operational efficiency, and enhance the overall employee experience.

What You Will Do

• Build and deploy AI agents, APIs, and applications on Affirm's internal platform (Snowpark Container Services / Quicksilver)
• Design and implement AI-powered solutions to solve complex business problems
• Collaborate with stakeholders to understand business requirements and identify opportunities for AI adoption
• Ensure the smooth operation of AI systems in production, including monitoring, maintenance, and troubleshooting
• Work closely with partners across the People function to integrate AI systems with existing tools and systems, such as Workday, Notion, and case management tools
• Develop and maintain the team's shared Python codebase, dbt models, and Snowflake infrastructure
• Design and implement reliability infrastructure for multi-model LLM services, including structured output validation, fallback chains, and circuit breakers for external APIs
• Contribute to the development of the team's technical architecture and strategy
• Participate in code reviews and ensure that all code is properly tested and validated before deployment
• Collaborate with non-technical stakeholders to scope problems, make architecture decisions, and provide honest assessments of what AI can and can't do

What We Are Looking For

• Software engineering foundation, with experience building, deploying, and maintaining production applications
• Strong understanding of systems thinking and technical architecture, with experience designing and implementing complex systems
• Experience with version control (Git/GitHub), CI/CD pipelines, containerization, and cloud-based infrastructure
• Strong programming skills in Python, with experience working with data structures, algorithms, and software design patterns
• Experience with machine learning and AI, including model development, training, and deployment
• Strong communication and collaboration skills, with experience working with non-technical stakeholders
• Ability to work independently and as part of a team, with a strong focus on delivering high-quality results
• Experience with Agile development methodologies and version control systems
• Strong understanding of data governance, security, and compliance, with experience working with sensitive data

Nice to Have

• Experience with Snowflake, Snowpark Container Services, and Quicksilver
• Experience with cloud-based infrastructure, including AWS, Azure, or Google Cloud
• Experience with containerization, including Docker and Kubernetes
• Experience with machine learning frameworks, including TensorFlow, PyTorch, or Scikit-Learn
• Experience with data visualization tools, including Tableau, Power BI, or D3.js

Benefits and Perks

• Competitive salary and benefits package
• Opportunity to work on cutting-edge AI and machine learning projects
• Collaborative and dynamic work environment
• Flexible working hours and remote work options
• Professional development opportunities, including training and conference sponsorships
• Access to the latest tools and technologies, including cloud-based infrastructure and machine learning frameworks
• Comprehensive health and wellness benefits, including medical, dental, and vision insurance
• Retirement savings plan, including 401(k) matching
• Generous paid time off and vacation policy
• Employee recognition and reward programs
• Opportunities for career growth and advancement

• To stand out in this role, focus on building a strong portfolio of AI and machine learning projects, including examples of your work with Python, data structures, and software design patterns.
• When applying, be sure to highlight your experience with version control, CI/CD pipelines, and cloud-based infrastructure, as well as your understanding of data governance, security, and compliance.
• In your resume and cover letter, use specific examples to demonstrate your ability to work independently and as part of a team, and your focus on delivering high-quality results.
• During the interview process, be prepared to discuss your experience with machine learning and AI, including model development, training, and deployment, as well as your understanding of systems thinking and technical architecture.
• When negotiating salary, be sure to research the market rate for AI Solutions Engineers in your area and be prepared to discuss your skills and experience in relation to the company's needs and expectations.
• Red flags to watch for in this role include a lack of clear communication from the hiring manager or team, or a lack of transparency around the company's goals and expectations.
• To prepare for the technical interview, practice coding challenges and whiteboarding exercises, and review your understanding of data structures, algorithms, and software design patterns.