Senior Software Engineer, Backend (AI Platform)

About the Role

The AI Platform team owns Affirm's paved path for building, running, evaluating, and governing AI systems. Our customers are Affirm users, every engineer, and a growing set of production workloads. The team builds and exposes governed interfaces to models, tools, and agents with identity, cost attribution, reliability, and security built in.

Key components owned by the team include the LLM Gateway fronting approved models (Claude, ChatGPT, open-weight models across AWS Bedrock and other providers), the MCP Gateway mediating and auditing tool calls, the Agent Runtime providing bounded execution for agentic workloads, and the evals and observability layer.

What You'll Do

• Plan, execute, and own technical decisions and projects within the AI Platform team, from design through launch and on-call.
• Design and build gateway, runtime, and evaluation services that take AI workloads from pilot to production, securely scaling across millions of users and transactions.
• Make AI spend attributable and governable: build identity, quota, routing, caching, and failover controls.
• Partner with security, infrastructure, and product engineering teams to set guardrails for agentic workloads and identity models for tool access.
• Create and monitor system metrics, owning operational health including alerting, runbooks, and on-call rotation.
• Set and improve code review and design standards across the team and broader engineering organization.
• Leverage AI tools and agentic workflows to accelerate code delivery, design review, and operations.
• Educate, mentor, and grow team members in design, coding, and testing best practices.

What We Look For

• 4+ years of experience designing, developing, and launching backend systems at scale using languages like Python or Kotlin.
• Track record of developing highly available distributed systems using technologies such as AWS, MySQL, and Kubernetes.
• Practical experience building with LLMs, agents, or AI frameworks in production (e.g., inference APIs, LLM gateways, MCP, tool calling, evals, agent runtimes).
• Solid understanding of AI usage and infrastructure needed to support and leverage AI workloads.
• Demonstrated ability to define clear technical plans and write clean, extensible, high-quality code.
• Proficiency in making safe, impactful modifications in large codebases.
• Strong verbal and written communication skills for cross-functional collaboration.
• Bachelor's degree in a related field or equivalent practical experience.