This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff AI Platform Engineer based in United States.

This is an exceptional opportunity to shape the technical foundation of next-generation AI products by building the platforms and infrastructure that enable teams to develop, deploy, and operate AI capabilities at scale. In this highly strategic role, you will work at the intersection of platform engineering, distributed systems, developer experience, and AI infrastructure. Rather than focusing on isolated AI features, you will create reusable frameworks, APIs, orchestration systems, and governance models that accelerate innovation across multiple teams. You will influence long-term architectural decisions, establish engineering standards, and develop scalable solutions that empower organizations to deliver reliable and production-ready AI experiences. This role is ideal for a senior technical leader who thrives on solving complex platform challenges and driving broad organizational impact.

• Architect and build the core AI platform, including reusable APIs, SDKs, shared services, and infrastructure components that standardize AI development practices.
• Develop modular agentic platform capabilities such as orchestration frameworks, workflow primitives, retrieval systems, tool interfaces, and context management solutions.
• Design and maintain evaluation infrastructure to support AI experimentation, testing, quality measurement, and CI/CD-integrated offline and online assessments.
• Establish platform standards, schemas, and interoperability frameworks that enable seamless integration between AI services, tools, and applications.
• Build highly scalable and reliable serving, routing, and control layers that optimize latency, availability, governance, and cost efficiency.
• Implement observability, tracing, auditing, and policy enforcement mechanisms to ensure AI systems remain measurable, secure, and production-ready.
• Drive platform adoption by creating developer-friendly tools, documentation, templates, and reference implementations.
• Collaborate with engineering and product leaders to identify recurring challenges and transform them into reusable organizational capabilities and best practices.
• Influence long-term AI platform strategy, architecture decisions, and engineering standards across the organization.

• 7+ years of experience in platform engineering, backend systems, AI/ML infrastructure, or developer tooling, with a strong focus on building shared platforms and scalable systems.
• Proven experience designing AI platform capabilities such as agent orchestration systems, evaluation frameworks, retrieval infrastructure, context engineering tools, or model-serving abstractions.
• Strong proficiency in Python and/or TypeScript, with expertise in distributed systems, asynchronous architectures, and resilient backend services.
• Extensive experience designing APIs, SDKs, service contracts, and extensible platform interfaces using technologies such as REST or gRPC.
• Deep understanding of modern AI frameworks and agentic systems, including the ability to abstract and operationalize AI capabilities at scale.
• Experience with production AI operational concerns, including model integration, latency optimization, reliability engineering, observability, and cost management.
• Strong background in Infrastructure as Code and cloud-native technologies, including Kubernetes, Docker, and Terraform.
• Familiarity with modern web technologies and developer ecosystems, including JavaScript, TypeScript, and React.
• Demonstrated ability to build reusable engineering standards, internal platforms, and "golden path" developer experiences.
• Excellent communication, leadership, and stakeholder management skills, with the ability to influence technical strategy across teams.
• Bachelor's degree in Computer Science, Engineering, or a related field; advanced degrees are considered an asset.
• Additional experience with agent frameworks, vector databases, model gateways, multi-tenant platform design, or enterprise governance frameworks is highly desirable.

• Competitive compensation package with base salary, performance incentives, and equity opportunities.
• Flexible paid time off policy promoting healthy work-life balance.
• Comprehensive health, dental, and vision coverage, including wellness and family support programs.
• Retirement savings plan with employer matching contributions.
• Paid family leave and medical leave programs.
• Employee stock options, allowing team members to share in organizational success.
• Wellness subsidy for fitness, health, and well-being initiatives.
• Access to mental health resources and employee support programs.
• Remote-first work environment with flexibility and occasional business travel opportunities.
• Long-term recognition programs and ongoing career development opportunities within a highly collaborative engineering culture.