Senior Software Engineer, Backend (AI Platform)

New

AffirmAI platform

Location: Remote USFull-TimeSenior

SalaryUSA base pay range (CA, WA, NY, NJ, CT) per year: $195,000 - 255,000; USA base pay range (all other U.S. states) per year: $173,000-233,000

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Job Details

Experience: 4+ years of experience designing, developing and launching backend systems at scale
Required Skills: AWSPythonKotlinKubernetesMySQLDistributed Systems

Have 4+ years of experience designing, developing, and launching backend systems at scale.
Have experience using backend languages such as Python or Kotlin.
Have a track record developing highly available distributed systems.
Have experience with technologies such as AWS, MySQL, and Kubernetes.
Have practical production experience building with LLMs, agents, or AI frameworks.
Have experience with inference APIs, LLM gateways such as LiteLLM or similar, MCP, tool calling, evaluations, or agent runtimes.
Understand AI usage and the infrastructure needed to support AI workloads across disciplines.
Have experience defining technical plans and delivering significant features or system components with elegant, simple, extensible designs.
Write high-quality code that is understandable and usable by others.
Be proficient in making significant changes in a large codebase and using tools and practices to do so safely.
Have a related bachelor’s degree or equivalent practical experience.

Plan and own AI Platform technical decisions and projects from design through launch and on-call.
Design and build gateway, runtime, and evaluation services to move AI workloads from pilot to production.
Build identity, quota, routing, caching, and failover controls for AI usage.
Partner with security, infrastructure, and product engineering teams to establish guardrails for agentic workloads and tool-access identity.
Create and monitor system metrics, and own monitoring, alerting, runbooks, and on-call.
Set and improve code review and design standards, and advocate for them through writing and tech talks.
Use AI tools and agentic workflows in coding, design review, and operations.
Educate and mentor engineers and drive design, coding, and testing practices.

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