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SpotifySpotifyNew York, NY

Senior Software Engineer - Enterprise AI

Build and operate secure enterprise AI platform infrastructure connecting models, agents, tools, and internal systems. The role requires strong backend engineering, API and integration design, identity and authentication experience, cloud infrastructure knowledge, and operational ownership.

Salary not listed
Remote5+ YOEBackend Engineering

About the role

Responsibilities

  • Design, build, and operate secure enterprise AI platform capabilities connecting AI models, agents, tools, and internal systems.
  • Own major enterprise AI infrastructure workstreams, including the Model Context Protocol (MCP) gateway and enterprise context capabilities, from technical design through launch and operation.
  • Build reliable backend services, APIs, and integrations for AI-powered workplace experiences.
  • Develop scalable AI governance approaches covering identity-aware access, permissions, auditing, policy enforcement, and risks from third-party AI-enabled tools.
  • Design, build, test, and evaluate agentic systems and workflows.
  • Take operational ownership of services and components, balancing speed, reliability, security, and maintainability.
  • Partner with engineers and stakeholders to identify opportunities, make technical tradeoffs, and turn emerging AI needs into scalable platform capabilities.
  • Contribute to engineering practices, knowledge sharing, and AI fluency.

Requirements

  • Strong software engineering fundamentals and experience building, testing, debugging, and operating reliable backend systems.
  • Experience with backend languages such as Python or Go.
  • Ability to design APIs and integrations across complex systems.
  • Understanding of software architecture and how services, APIs, enterprise tools, and user-facing experiences fit together.
  • Experience with identity and authentication concepts and technologies such as OAuth, SAML, or SCIM.
  • Experience working with cloud infrastructure.
  • Comfort navigating ambiguity, creating clarity, and making thoughtful technical tradeoffs.
  • Commitment to operational ownership and dependable infrastructure.
  • Collaborative mindset with an interest in experimentation, iteration, knowledge sharing, and continuous learning.

Nice-to-haves

  • Google Cloud Platform familiarity.
  • Experience with enterprise SaaS or platform engineering.
  • Experience with LLM integration patterns such as tool use, function calling, agentic workflows, or systems-level prompt engineering.

Skills

PythonGoAPIsOAuthSAMLSCIMGCPmcpllm integrationAgentic Workflowsfunction callingCloud Infrastructure

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