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StackAI

Low-code platform to build AI workflows

Platform Engineer - APIs & Observability

Backend EngineeringConfirmed live in the last 24 hours
Full-time$171k - $190k /yrHybrid

About the Job

Requirements

  • At least 4 years of experience building backend services and public APIs in production.
  • Strong API design skills, including RESTful design, SDK ergonomics, and rate limiting.
  • Fluency with OpenAPI and experience defining API standards and governance, including versioning, deprecation, and consistency across services.
  • Fluency with observability and analytics, including distributed tracing, metrics, and turning raw signals into dependable data products.
  • Strong Python skills and experience with modern backend frameworks such as FastAPI or similar.
  • Comfort working across TypeScript and Node.js on product surfaces.

Responsibilities

  • Design, version, and evolve the public API and SDKs used by StackAI customers while maintaining a high-quality developer experience.
  • Define API conventions, versioning and deprecation policies, and review standards to keep APIs across the platform consistent and predictable.
  • Build tracing and instrumentation so users can follow an agent run end to end across its models, tools, and sub-agents.
  • Build reporting that helps customers understand agent performance, costs, and opportunities for improvement.
  • Build audit logging and team-scoped views for enterprise customers.

Desired Qualifications

  • Experience with OpenTelemetry or distributed tracing at scale.
  • Experience with analytics datastores such as ClickHouse, Druid, or similar.
  • Experience designing developer-facing SDKs for external customers.
  • AI or large language model platform experience, including token and cost accounting or agent-run tracing.
  • Startup or growth-stage experience.

About the Company

StackAI

Low-code platform to build AI workflows

Stack AI provides an enterprise-focused, no-code platform for building and deploying custom AI agents and workflow automations. Its product uses a visual drag-and-drop interface to connect data sources and large language models with enterprise systems, enabling users to create knowledge assistants, contract analysis, RFP responses, due diligence, and document data extraction without deep coding. The platform differentiates itself with enterprise deployment options (including on-premise), compliance (SOC 2, GDPR, HIPAA), and tiered pricing, aimed at rapid deployment to boost back-office productivity. Its goal is to help organizations maximize model accuracy and reduce deployment times by bridging corporate data with LLM capabilities to automate business processes.

Company size
51-200
Company stage
Series A
Total funding
$19.1M
Headquarters
San Francisco, CA
Founded
2021

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