• Lead Natera’s infrastructure as the Manager of Platform Engineering. • Oversee Cloud Engineering, Orchestration and Kafka workstreams. • Define and execute the roadmap for Cloud, Orchestration, and Kafka ecosystems. • Ensure high internal satisfaction by treating the platform as a world-class product. • Manage and mentor a high-performing team of engineers. • Facilitate cross-functional collaboration with stakeholders.

Role Description The role will require you to join Tensordyne’s Platform Software team, to lead the requirements gathering, ideation and creation of system level tests and tools for Tensordyne’s AI inference system diagnostics, debugging, and analysis software. The successful candidate will support cross-functional engineering teams in the bring-up and validation of platform software on AI inference systems, as well as working closely with Tensordyne’s manufacturing test team, to ensure that they can automate the system diagnostic tools and tests that you create, via production test scripts and manufacturing diagnostics packages. Qualifications - 5+ years of experience developing low-level platform software tools and manufacturing diagnostics for high performance compute systems deployed to data center customers. - Expert programming experience in C++, Python, Bash/Shell, Tcl/Expect, and/or related programming languages. - Hands-on experience bringing up and debugging complex Linux-based systems; a familiarity with AI inference frameworks and data center deployment/management environments is preferred. - Self-motivated, adaptable, and comfortable working across hardware, software, and manufacturing teams in a fast-paced startup environment. - Excellent technical communication skills, with the ability to clearly explain complex technical concepts and practical solutions. - BS or MS degree in Electrical Engineering, Computer Science, or a related technical field. - Travel to contract manufacturer sites, as needed, to support test station bring-up, troubleshoot production failures in the manufacturing environment. Company Description Tensordyne is an AI system solution company that builds very high-performance, low-power generative AI inference systems. Our mission, through the creation of custom silicon, hardware and software, is to enable multimodal Generative AI inference acceleration at scale, with safe, sustainable, high-performance systems for our hyperscaler and neocloud data center customers. We are at the leading edge of advancing the latest research and product improvements for generative AI inference solutions that will make AI even more advantageous for compelling new generative AI applications. Tensordyne is a well funded, fast-paced startup company with headquarters in both Sunnyvale, CA, and Munich, Germany. We also have many talented team members working remotely across North America and Europe. We take care of our people and their families with comprehensive benefits, competitive compensation, flexible spending options, and recognition programs, because building category-defining technology starts with a healthy, supported team. Come join us as we shape the future of multimodal generative artificial intelligence!

Role Description The AI Platform Engineer is responsible for designing, building, and operationalizing the organization's AI platform capabilities across cloud infrastructure, enterprise systems, and customer-facing digital platforms. This role serves as a technical leader within the IT organization and partners closely with Digital Development, Enterprise Systems, Operations, and business stakeholders to create scalable, secure, and reusable AI-enabled platform services that enhance both internal operations and external digital user experiences. A core function of this role is establishing and evolving the organization's AI Service Layer and supporting platform architecture including: - AI orchestration services - Reusable APIs - Customer-specific deployment models - Scalable cloud-native platform services This role bridges AI engineering, cloud architecture, SaaS platform engineering, DevOps collaboration, and enterprise data enablement to ensure AI capabilities can be consistently deployed, integrated, governed, and scaled across both enterprise operations and customer-facing digital platform experiences. Responsibilities - AI Platform Architecture & Engineering: - Design, develop, and maintain reusable AI platform services and infrastructure components that support enterprise AI initiatives and customer-facing digital platforms, including AI APIs, orchestration services, retrieval-augmented generation (RAG) pipelines, prompt management, vector search capabilities, model integration frameworks, and reusable backend AI services. - Digital Platform AI Enablement: - Design and implement AI capabilities that enhance customer-facing digital platforms and SaaS applications, including intelligent workflows, conversational interfaces, recommendation systems, predictive insights, automation services, and AI-assisted user experiences. - Partner closely with frontend, backend, and UX teams to ensure AI capabilities are seamlessly integrated into unified digital platform experiences. - AI Service Layer Development: - Build and maintain a centralized AI Service Layer that standardizes how enterprise systems, digital platforms, and SaaS applications consume AI capabilities, ensuring reusable patterns for model access, prompt orchestration, logging, security, governance, and scalable AI integration across customer-facing and internal solutions. - Enterprise Data & AI Enablement: - Partner closely with Data Integrations Engineering and Enterprise Systems teams to ensure enterprise data assets are accessible, structured, secure, normalized, and optimized for AI and analytics workloads across both internal and customer-facing systems. - SaaS Platform Architecture & Deployment Support: - Support scalable multi-tenant and customer-specific SaaS deployment models, including customer environment provisioning standards, AI service deployment architecture, database isolation strategies, deployment automation, and platform scalability best practices. - Technical Leadership & Cross-Functional Collaboration: - Collaborate closely with DevOps, Backend Engineering, Data Integrations, Enterprise Systems, Frontend Development, and UI/UX teams to define scalable AI integration standards, reusable AI-enabled development patterns, and AI platform best practices across the organization. - Partner with business departments including Operations, Sales, R&D, and other functional teams to identify opportunities for AI-enabled process improvement, intelligent automation, predictive insights, and enhanced digital platform capabilities that align with organizational objectives and operational needs. Qualifications - Bachelor's degree in Computer Science, Software Engineering, Artificial Intelligence, Data Engineering, or related field. - 5+ years of experience in AI engineering, machine learning engineering, AI platform development, or related technical roles. - Demonstrated experience building and deploying AI-enabled applications, AI services, or customer-facing AI capabilities in production environments. - Strong proficiency in Python, SQL, REST APIs, and AI service development. - Experience designing and deploying AI/ML services using Azure, Anthropic, vector databases, or related AI tooling. - Experience integrating AI capabilities into customer-facing web applications, SaaS products, or digital platform experiences. - Familiarity with scalable SaaS application architectures, API integration patterns, and AI orchestration workflows. - Familiarity with relational databases, secure data access concepts, and customer-aware data architectures. - Strong analytical, systems-thinking, and problem-solving capabilities. - Ability to clearly communicate technical concepts and AI solution designs to both technical and non-technical stakeholders. - Ability to work independently and collaboratively within cross-functional teams including Backend Engineering, Frontend Development, DevOps, Data Integrations, and UI/UX. - Willingness to travel occasionally (approximately 10%). Preferred - Master's degree in Computer Science, Artificial Intelligence, Data Engineering, or related field. - Experience building enterprise AI service layers, AI orchestration platforms, or reusable AI-enabled application services. - Experience integrating AI capabilities into customer-facing SaaS applications or digital platform experiences. - Experience with Azure AI Services, Azure Functions, Azure SQL, Azure Data Factory, Event Grid, Service Bus, or related Azure platform services. - Experience working within scalable SaaS application environments and customer-aware deployment models. - Experience with observability, monitoring, logging, and operational support for AI-enabled services. - Experience implementing secure AI governance, model access controls, and operational AI best practices. - Experience mentoring engineers or providing technical leadership across cross-functional development teams. - Relevant Azure, AI, or cloud-related certifications. Company Description USALCO is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected veteran status, age, or any other characteristic protected by law. As a general policy, USALCO does not offer employment visa sponsorships upon hire or in the future.

• Craft fault-tolerant data pipelines and distributed systems to support millions of students. • Effective communicator who collaborates well with distributed engineering, product, and design teams; experience explaining data architecture to both technical and non-technical audiences. • Ensure that timely, accurate data and metrics are delivered consistently. • Partner with your peer engineers and product owners on getting features and products to market. • Evolve data ownership and fluency across our teams, allowing us to bring new insights to customers easily and cost-effectively.