AI Solutions Engineer

About the Job

Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest.

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About The Team

People Tech & Analytics (PTA) builds and owns the data, AI, and technology infrastructure for Affirm's People function. The team runs like a product engineering group embedded in HR. We own the full stack: data ingestion, transformation, dashboards, AI tools, and production applications deployed on Snowflake.

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About The Role

This is a hands-on engineering role. You will build, deploy, and maintain AI-powered systems that serve the People function and the broader employee base. The work is taking messy business problems (fragmented knowledge, manual processes, disconnected tools) and turning them into working software: agents, APIs, applications, and infrastructure.

You will work closely with partners across the People function who own domain expertise and stakeholder relationships. Your job is to turn their rough applications and processes into production systems, and to push back when a technical constraint changes what's possible. This is not a pure backend role. You will be in the room when business problems are being scoped, and you need to understand the problem well enough to make architecture decisions on your own. You also need to take what you build and get it running in production. Hosting, security, deployment, and ongoing maintenance are all part of the job.

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What You'll Do

• Build and ship AI agents, APIs, and applications on Affirm's internal platform (Snowpark Container Services / Quicksilver). You own the full lifecycle: architecture, containerization, networking, secrets, CI/CD, monitoring, and fixing what breaks
• Turn messy business requirements from People Operations stakeholders into production systems. Integrate with Workday, Notion, and case management tools so AI surfaces real answers from governed content, not model guesses
• Navigate Affirm's existing security and data governance infrastructure to get AI systems running safely on people data. Figure out RBACs, data classification, and access policies across Workday, Snowflake, and case tools to make sure employee data stays secure
• Design reliability infrastructure for multi-model LLM services: structured output validation, fallback chains, circuit breakers for external APIs, and quality controls that catch hallucination before users see it
• Work directly with non-technical stakeholders to scope problems, make architecture decisions, and translate technical constraints into business language (and vice versa)
• Contribute to the team's shared Python codebase, dbt models, and Snowflake infrastructure as part of a small, full-stack team that ships fast
• Own what you build. When something breaks in production, you diagnose and fix it

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What We're Looking For

• Software engineering foundation: You have built, deployed, and maintained production applications. You understand version control (Git/GitHub), CI/CD pipelines, containerization, and what it takes to keep software running, not just written
• Systems thinking and technical architecture: You understand how software systems fit together (databases, APIs, authentication, hosting, deployment pipelines). You can make architecture decisions, evaluate trade-offs, and read code well enough to know when something is wrong. You should be comfortable in Python, but the ability to think in systems matters more than raw coding skill
• Builder disposition: You have created something from nothing (a system, a tool, a platform) in an environment where nobody handed you a spec. You identified the problem, designed the solution, and shipped it
• Ability to work across the technical-business boundary: You can sit in a meeting with non-technical stakeholders, understand the real problem behind the stated request, and come back with a solution that actually addresses it

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Why You'll Love This Role

• You will build AI systems that directly change how 2,000+ employees interact with the People function with visible, measurable impact
• Small team, high autonomy. You own what you build, from architecture through production
• Work at the frontier of AI-powered employee experience—the kind of work that will define how companies operate in the next five years
• A team that ships fast, uses AI tools as a core part of how we work, and doesn't wait for permission to build things

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Compensation, Location & Benefits

Pay Grade: O

Equity Grade: 12

*Employees new to Affirm typically come in at the start of the pay range. Please note that visa sponsorship is not available for this position.*

• USA base pay range (CA, WA, NY, NJ, CT): $220,000 - $280,000 per year
• USA base pay range (all other U.S. states): $195,000 - $255,000 per year

Affirm is proud to be a remote-first company! The majority of our roles are remote and you can work almost anywhere within the country of employment. Affirmers in proximal roles have the flexibility to work remotely, but will occasionally be required to work out of their assigned Affirm office.

Key Benefits Highlights:

• Health care coverage: Affirm covers 100% of all premiums for all levels of medical, dental, and vision coverage for you and your dependents
• Flexible Spending Wallets: Generous monthly stipends for spending on Technology, Food, Lifestyle needs, and family forming expenses
• Time off: Competitive vacation and holiday schedules allowing you to rest and recharge
• ESPP: An employee stock purchase plan enabling you to buy shares of Affirm at a discount

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Equal Opportunity & Inclusive Hiring

We believe *It’s On Us* to provide an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process.

*[For U.S. positions that could be performed in Los Angeles or San Francisco]* Pursuant to the San Francisco Fair Chance Ordinance and Los Angeles Fair Chance Initiative for Hiring Ordinance, Affirm will consider for employment qualified applicants with arrest and conviction records.