[All remote jobs](https://jobicy.com/jobs.md)[![Spotify logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2021/03/Jobicy-210328105941-289246.jpg)](https://jobicy.com/company/spotify.md)[Spotify](https://jobicy.com/company/spotify.md) # Senior Software Engineer – Enterprise AI Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move. [Apply for this job](#job-application)[View company](https://jobicy.com/company/spotify.md)ShareRemote from[USA](https://jobicy.com/job-region/usa.md)SalaryUSD 164,448–234,926 / yrDepartment[Software Engineering](https://jobicy.com/categories/engineering.md)EmploymentFull TimeExperienceSeniorPublished1 Nov 2026Apply before1 Dec 2026Listing views59Application actions4Application toolkit ## Make your next move. Prepare your resume, explore your fit, and draft a cover letter for this opportunity. AI Summary ## The role, at a glance. Spotify is seeking a senior backend/platform engineer to build and operate enterprise AI infrastructure for internal users. The role owns secure integrations among AI models, agents, internal systems, and services such as an MCP gateway. Key work includes API and backend-service development, identity-aware access controls, governance, auditing, and reliable operation of AI-enabled workflows. The engineer will make architectural tradeoffs, partner across the company, and take end-to-end ownership from design through production operations. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 5/5EasyHard ### Pace & Pressure 4/5RelaxedFast-paced ### Autonomy Level 5/5GuidedFull ownership ### Communication Load 4/5IndependentCollaborative AI insightThis is a senior-level platform role combining distributed backend engineering, AI integration patterns, security governance, and operational ownership. It requires independently resolving ambiguous technical problems while building dependable systems used across a large organization. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job median (per year)Market rate$199,687US market range (per year)$170k–$245k0$269.50k AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. The employer discloses a US base-pay range of $164,448–$234,926 USD. Although the posting does not explicitly state a pay cadence, yearly compensation is inferred from the magnitude, US market, senior full-time engineering context, and stated base range. The midpoint is $199,687 per year; the estimated US market range for comparable senior enterprise AI platform engineering roles is $170,000–$245,000 per year. ## Core skills Skills and capabilities most closely associated with this opportunity. [Backend engineering](https://jobicy.com/jobs?search_keywords=Backend%20engineering.md)[Python](https://jobicy.com/jobs?search_keywords=Python.md)[Go](https://jobicy.com/jobs?search_keywords=Go.md)[API design](https://jobicy.com/jobs?search_keywords=API%20design.md)[Enterprise AI platforms](https://jobicy.com/jobs?search_keywords=Enterprise%20AI%20platforms.md)[Model Context Protocol](https://jobicy.com/jobs?search_keywords=Model%20Context%20Protocol.md)[LLM integration](https://jobicy.com/jobs?search_keywords=LLM%20integration.md)[Agentic workflows](https://jobicy.com/jobs?search_keywords=Agentic%20workflows.md)[OAuth](https://jobicy.com/jobs?search_keywords=OAuth.md)[SAML](https://jobicy.com/jobs?search_keywords=SAML.md)[SCIM](https://jobicy.com/jobs?search_keywords=SCIM.md)[Identity and access management](https://jobicy.com/jobs?search_keywords=Identity%20and%20access%20management.md)[Google Cloud Platform](https://jobicy.com/jobs?search_keywords=Google%20Cloud%20Platform.md)[Cloud infrastructure](https://jobicy.com/jobs?search_keywords=Cloud%20infrastructure.md)[AI governance](https://jobicy.com/jobs?search_keywords=AI%20governance.md) Sample interview questionsHow would you design an MCP gateway that securely exposes internal tools and context to AI agents?I would start with a threat model and define clear trust boundaries between agents, the gateway, tools, and internal data sources. The gateway would enforce identity-based authentication and authorization, scoped tool permissions, input and output validation, audit logging, rate limits, and policy checks. I would also design for tenant or team isolation, secret management, observability, and safe failure modes. Describe how you would evaluate the reliability of an agentic workflow in production. I would define task-success, correctness, latency, cost, and safety metrics before deployment. Evaluation would combine curated offline test cases, adversarial scenarios, staged rollouts, and production telemetry such as tool-call failures, retries, user corrections, and policy violations. I would use the findings to improve prompts, tool contracts, guardrails, and fallback paths. What tradeoffs would you consider when integrating a third-party AI service into an enterprise platform? I would assess data handling, retention, model access, vendor security controls, availability, latency, cost, and lock-in risk. The integration should minimize shared data, apply strong access controls, log use appropriately, and isolate provider-specific logic behind stable internal interfaces. I would also plan fallback behavior and governance controls for changes in vendor capabilities or policies. How have you approached operational ownership for a backend service? I treat production readiness as part of delivery by defining service-level objectives, dashboards, alerts, runbooks, capacity expectations, and incident procedures. I build for debuggability with structured logs, tracing, meaningful metrics, and safe deployment and rollback processes. After launch, I review incidents and operational signals to prioritize reliability improvements. How would you implement identity-aware authorization across APIs used by internal AI tools? I would use standards-based authentication such as OAuth or SAML-backed identity, then propagate verified user and service identity through calls. Authorization would be centrally policy-driven and evaluated at the resource and action level, with least-privilege scopes and auditable decisions. For sensitive operations, I would add explicit approval, stronger verification, and comprehensive audit trails. Opportunity details ## About this role. The Platform team creates the technology that enables Spotify to learn quickly and scale easily, enabling rapid growth in our users and our business around the globe. Spanning many disciplines, we work to make the business work; creating the infrastructure, tooling, frameworks, and capabilities needed to welcome a billion customers. Enterprise AI builds and operates the internal AI platform layer that supports Spotifiers across the company. We’re helping evolve AI tooling into reliable infrastructure that teams can use in their day-to-day work. Our team builds the connective tissue between AI models and Spotify’s internal systems, with a focus on secure access, governance, identity, integrations, and dependable AI infrastructure. ### What You’ll Do * Design, build, and operate secure enterprise AI platform capabilities that connect AI models, agents, tools, and Spotify’s internal systems. * Own major workstreams across our enterprise AI infrastructure, including our Model Context Protocol (MCP) gateway and enterprise context capabilities, from technical design through launch and operation. * Build reliable backend services, APIs, and integrations that enable AI-powered experiences across Spotify’s digital workplace. * Help develop scalable approaches to AI governance, including identity-aware access, permissions, auditing, policy enforcement, and managing risks associated with third-party AI-enabled tools. * Design, build, test, and evaluate agentic systems and workflows that help Spotifiers access information and accomplish tasks effectively. * Take operational ownership of the services and components you build, balancing speed, reliability, security, and long-term maintainability. * Partner with engineers and stakeholders across Spotify to identify opportunities, make thoughtful technical tradeoffs, and turn emerging AI needs into scalable platform capabilities. * Contribute to engineering practices, knowledge sharing, and AI fluency as we learn how to operate enterprise AI infrastructure at Spotify scale. ### Who You Are * You have strong software engineering fundamentals and experience building, testing, debugging, and operating reliable backend systems. * You are experienced with backend languages such as Python, Go, or similar and are comfortable designing APIs and integrations across complex systems. * You understand software architecture and how services, APIs, enterprise tools, and user-facing experiences fit together. * You have experience with identity and authentication concepts and technologies such as OAuth, SAML, or SCIM. * You have experience working with cloud infrastructure; familiarity with Google Cloud Platform is valuable. * You are comfortable navigating ambiguity, creating clarity, and independently making thoughtful technical tradeoffs. * You care about operational ownership and building dependable infrastructure that other teams and employees can rely on. * You enjoy experimentation, iteration, knowledge sharing, and continuous learning in a collaborative engineering environment. * Experience with enterprise SaaS or platform engineering, or with LLM integration patterns such as tool use, function calling, agentic workflows, or systems-level prompt engineering, will help you make an impact in this role. ### Where You’ll Be * This role is based in New York. * We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home. ### Compensation ### Additional Information The United States base range for this position is $164,448–$234,926 USD, plus equity. The benefits available for this position include health insurance, six-month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, paid flexible holidays, and paid sick leave. These ranges may be modified in the future. Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens. At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know – we’re here to support you in any way we can. 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