We're looking for a Backend Engineer to help bring large-scale GenAI systems to production. In this role, you'll build the core infrastructure that powers AI products for some of the world's largest enterprises,designing scalable APIs, distributed data systems, and robust deployment pipelines that enable production-grade reliability and performance.

This is a rare opportunity to be at the center of the GenAI revolution, solving hard backend and infrastructure challenges that make AI truly work at enterprise scale. If you're excited about shaping how AI systems are deployed and scaled in the real world, we want to hear from you.

At Scale, we don't just follow AI advancements , we lead them. Backed by deep expertise in data, infrastructure, and model deployment, we are uniquely positioned to solve the hardest problems in AI adoption. Join us in shaping the future of enterprise AI, where your work will directly impact how businesses operate, innovate, and grow in the age of GenAI.

Responsibilities

• Design, build, and scale backend systems that power enterprise GenAI products, focusing on reliability, performance, and deployment across both Scale's and customers' infrastructure.

• Develop core services and APIs that integrate AI models and enterprise data sources securely and efficiently, enabling production-scale AI adoption.

• Architect scalable distributed systems for data processing, inference, and orchestration of large-scale GenAI workloads.

• Optimize backend performance for latency, throughput, and cost,ensuring AI applications can operate at enterprise scale across hybrid and multi-cloud environments.

• Manage and evolve cloud infrastructure (AWS, Azure, or GCP), driving automation, observability, and security for large-scale AI deployments.

• Collaborate with ML and product teams to bring cutting-edge GenAI models into production through efficient APIs, model serving systems, and evaluation frameworks.

• Continuously improve reliability and scalability, applying strong engineering practices to make AI systems robust, maintainable, and enterprise-ready.

Ideal Candidate

• 4+ years of experience developing large-scale backend or infrastructure systems, with a strong emphasis on distributed services, reliability, and scalability.

• Proficiency in Python or TypeScript, with experience designing high-performance APIs and backend architectures using frameworks such as FastAPI, Flask, Express, or NestJS.

• Deep familiarity with cloud infrastructure (AWS and Azure preferred), including container orchestration (Kubernetes, Docker) and Infrastructure-as-Code tools like Terraform.

• Experience managing data systems such as relational and NoSQL databases (PostgreSQL, DynamoDB, etc.) and building pipelines for data-intensive applications.

• Hands-on experience with GenAI applications, model integration, or AI agent systems,understanding how to deploy, evaluate, and scale AI workloads in production.

• Strong understanding of observability, CI/CD, and security best practices for running services in enterprise or multi-tenant environments.

• Ability to balance rapid iteration with production-grade quality, shipping reliable backend systems in fast-paced environments.

Collaborative mindset, working closely with ML, infra, and product teams to bring complex GenAI systems into production at enterprise scale.

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You will have a strong track record of writing clean, efficient, maintainable, and scalable code in Python or Rust, and a deep interest in voice/audio AI. You will also have hands-on experience shipping features on iOS and/or Android, and the ability to work across all product groups and do whatever it takes for best user experience.

In this role, you will collaborate directly with Grok Voice model, media, and product teams to deliver end-to-end experiences, and drive performance, reliability, and quality of voice interactions at global scale. You will also have the opportunity to participate in a flat organisational structure, where leadership is given to those who show initiative and consistently deliver excellence.

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We're looking for an experienced Engineering Manager to lead our Agent Experience team. As a key member of our engineering organization, you will be responsible for scaling a mission-critical team from its early stages. You will balance deep technical strategy in the AI space with a relentless bias-for-action, ensuring we ship high-leverage tools for developers and their agents.

Responsibilities

• Lead and scale a high-performing team of 10+ engineers, ranging from early-career to Staff level.
• Define agentic strategy and partner with product and executive leadership to shape the long-term vision of how AI agents consume Stripe's APIs and services.
• Foster a 'bias-for-action' culture that allows the team to ship rapidly in an evolving market without sacrificing the reliability expected of financial infrastructure.
• Oversee the design and delivery of complex back-end systems and developer tools, ensuring they are extensible, secure, and intuitive for both humans and agents.
• Collaborate cross-functionally and act as a primary bridge between your team and Stripe's senior leadership, influencing company-wide strategy for AI integration and agentic workflows.

Requirements

• 5+ years of engineering management experience, with a proven track record of managing and growing teams of 10+ engineers.
• Deep domain expertise in the Agentic AI space or a strong background in building sophisticated developer tools and back-end systems.
• Exceptional communication skills, with the ability to distill complex technical concepts into clear strategic frameworks for peers and executives.
• Experience in rapid-growth environments, specifically a history of successful, high-volume hiring and team scaling.
• Technical proficiency to engage deeply with Staff-level engineers on system architecture, API design, and AI model integration.

Preferred Qualifications

• A 'dual-track' career history with experience in both early-stage startups and high-growth, at-scale technology companies.
• Experience navigating high-stakes, regulated industries such as Fintech or Healthcare.
• A strong point of view on the future of AI-driven economies and the 'agentic' evolution of software.

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