Kubernetes AI Jobs

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Ship critical infrastructure managing real-world logistics and financial data for the largest enterprise in the world. Own the why by building deep context through customer calls and understanding the company's value to customers, pushing back on requirements if a better, faster solution is seen. Demonstrate full-stack proficiency by working across system boundaries, including frontend UX, LLM agents, database schema, and event infrastructures. Leverage AI tools to automate boilerplate so focus can be on quality, architecture, and product taste. Constantly raise the velocity bar by optimizing development loops, refactoring legacy patterns, automating workflows, and fixing broken processes.

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As a Forward Deployed Engineer Lead, you will own the end-to-end technical strategy, execution, and delivery of complex agentic applications, from early pre-sales discovery through production deployment. Responsibilities include partnering with Deployment Strategists and Sales to understand enterprise customer needs, architecting solutions, and developing transformative agentic applications. You will architect and build complex agentic systems using state-of-the-art models, orchestrate sophisticated LLM workflows, and integrate deeply with enterprise infrastructure. Collaboration with research teams to adapt and fine-tune models for customer-specific needs and contributing to the internal codebase for inference, fine-tuning, and evaluation is required. You will own end-to-end deployments across hybrid environments including public cloud, VPC, and on-premises, ensuring production-grade scalability, performance, and reliability. Additionally, you will shape and scale the Forward Deployed Engineering organization by defining playbooks, best practices, technical standards, and providing mentorship to support team growth.

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As a Forward Deployed Engineer at Reflection, you will partner with Deployment Strategists and Sales to understand enterprise customer needs, architect solutions, and develop transformative agentic applications. You will build agentic systems using state-of-the-art models, orchestrate LLM workflows, integrate with enterprise infrastructure, and deploy reliable production systems. You will collaborate with research teams to adapt and fine-tune models for customer-specific needs. You will support end-to-end deployments across hybrid environments such as public cloud, VPC, and on-premises, ensuring scalability, performance, and reliability in production. Additionally, you will contribute to evolving playbooks, processes, and best practices as part of the growing Forward Deployed Engineering organization.

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As a Production AI Ops Lead, you will design and develop the production lifecycle of full-stack AI applications, support end-to-end system reliability, real-time inference observability, sovereign data orchestration, high-security software integration, and resilient cloud infrastructure for international government partners. You will own the production outcome, taking full accountability for the long-term performance and reliability of AI use cases deployed across international government agencies. You will ensure full-stack integrity by overseeing the health of the platform, ensuring seamless integration between the AI core and all full-stack components from APIs to UI. Additionally, you will build automated systems to monitor model performance and data drift across geographically dispersed environments, manage the technical lifecycle within diverse regulatory frameworks, lead the response for production issues in mission-critical environments, translate deep technical performance metrics into clear insights for senior international government officials, and partner with Engineering and ML teams to ensure field lessons influence future technical architecture and decisions.

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Lead efforts to drive the design and development of customer-facing multi-modal machine learning inference systems. Work with the Platform and Inference teams on building inference systems for the next generation of models, focusing on optimization, model tuning, and deployment. Partner with leading cloud providers to deliver hosted Stability AI inference solutions. Serve as a strategic thought partner for leaders across the organization on driving business impact through machine learning. Contribute to bringing new Stability models and pipelines into existence. Prototype and productionize inference platform improvements and new features.

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The Production AI Ops Lead is responsible for designing and developing the production lifecycle of full-stack AI applications, supporting system reliability, real-time inference observability, sovereign data orchestration, secure software integration, and resilient cloud infrastructure for international government partners. They own the production outcome, taking full accountability for the long-term performance and reliability of AI use cases deployed across international government agencies. They oversee the end-to-end health of the platform, ensuring seamless integration between the AI core and all full-stack components from APIs to UI, maintaining a responsive and production-ready environment. The role involves building automated systems to monitor model performance and data drift across geographically dispersed environments to ensure reliability, managing the technical lifecycle within diverse regulatory frameworks, and leading incident response for production issues in mission-critical environments to ensure rapid resolution and prevent recurrence. The lead also translates technical performance metrics into clear insights for senior international government officials and partners with Engineering and ML teams to influence the technical architecture and decisions of future AI use cases.

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As a Production AI Ops Lead, you will design and develop the production lifecycle of full-stack AI applications while supporting end-to-end system reliability, real-time inference observability, sovereign data orchestration, high-security software integration, and resilient cloud infrastructure for international government partners. You will take full accountability for the long-term performance and reliability of AI use cases deployed across international government agencies. You will oversee the end-to-end health of the platform, ensuring seamless integration between the AI core and all full-stack components from APIs to UI, maintaining a responsive and production-ready environment. You will build automated systems to monitor model performance and data drift across geographically dispersed environments to ensure reliability. You will manage the technical lifecycle within diverse regulatory frameworks and lead the response for production issues in mission-critical environments, ensuring rapid resolution and building guardrails to prevent recurrence. You will translate deep technical performance metrics into clear insights for senior international government officials and partner with Engineering and ML teams to ensure lessons learned influence future technical architecture and decisions.

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As a Production AI Ops Lead, you will design and develop the production lifecycle of full-stack AI applications, supporting end-to-end system reliability, real-time inference observability, sovereign data orchestration, high-security software integration, and resilient cloud infrastructure for international government partners. You will own the production outcome by taking full accountability for the long-term performance and reliability of AI use cases deployed across international government agencies. You will ensure full-stack integrity by overseeing the end-to-end health of the platform, ensuring seamless integration between the AI core and all full-stack components from APIs to UI to maintain a responsive and production-ready environment. You will build automated systems to monitor model performance and data drift across geographically dispersed environments, ensuring reliability. You will manage the technical lifecycle within diverse regulatory frameworks and lead the response for production issues in mission-critical environments to ensure rapid resolution and build guardrails to prevent recurrence. You will translate deep technical performance metrics into clear insights for senior international government officials and partner with Engineering and ML teams to ensure lessons learned influence the technical architecture and decisions of future use cases.

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As an AI Infrastructure Engineer, the responsibilities include participating in an on-call rotation to respond to production incidents, building and running infrastructure using Ansible, Terraform, and Kubernetes to enable scaling for many concurrent users, building monitoring systems to ensure high-quality service, designing and implementing operational processes such as deployments and upgrades, debugging production issues across all services and stack levels, identifying improvements for product architecture concerning reliability, performance, and availability, and planning the growth of Together AI's infrastructure.

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As a Production AI Ops Lead, you will design and develop the production lifecycle of full-stack AI applications, while supporting end-to-end system reliability, real-time inference observability, sovereign data orchestration, high-security software integration, and the resilient cloud infrastructure required for international government partners. You will own the production outcome by taking full accountability for the long-term performance and reliability of AI use cases deployed across international government agencies. You will ensure full-stack integrity by overseeing the end-to-end health of the platform, ensuring seamless integration between the AI core and all full-stack components, from APIs to UI, to maintain a responsive and production-ready environment. You will scale the feedback loop by building automated systems to monitor model performance and data drift across geographically dispersed environments, ensuring the right levels of reliability. You will manage the technical lifecycle within diverse regulatory frameworks to navigate global compliance. You will lead the response for production issues in mission-critical environments as incident command, ensuring rapid resolution and building guardrails to prevent recurrence. You will translate deep technical performance metrics into clear insights for senior international government officials, and drive product evolution by partnering with Engineering and ML teams to ensure lessons learned in the field influence the technical architecture and decisions of future use cases.