Principal Engineer – AI Platform Architecture

📍 Location: Remote 🎓 Education: Bachelor's or Master's degree in Computer Science, Software Engineering, Information Systems, or a related field 🌐 English: Fluent (mandatory) About the Role: We are looking for a Principal Engineer – AI Platform Architecture to provide hands-on technical leadership in the design and evolution of a next-generation AI platform. This is a highly senior individual contributor role focused on architecture, engineering standards, platform evolution, and technical leadership. The position does not include people management responsibilities but requires close collaboration and influence across Product Engineering, Platform Engineering, Data, Security, and Product Management teams. The successful candidate will help define how agent runtimes, orchestration capabilities, APIs, platform services, observability, developer tooling, and engineering standards align to support the organization's AI strategy and long-term platform vision. Minimum Experience ✔ Proven experience designing large-scale software platforms and distributed systems ✔ Experience defining and driving architectural standards across multiple engineering teams ✔ Strong background in cloud-native application architecture and modern engineering practices ✔ Experience building reusable platform capabilities and shared engineering services ✔ Experience operating across infrastructure, applications, AI systems, and product engineering environments Key Requirements - Experience designing large-scale software platforms and distributed systems. - Strong understanding of cloud-native application architecture and modern engineering practices. - Demonstrated success establishing technical standards across multiple engineering teams. - Solid software engineering background with experience building reusable platform capabilities. - Hands-on expertise with microservices, APIs, asynchronous systems, and event-driven architectures. - Experience mentoring senior engineers through technical leadership. - Comfortable working across infrastructure, applications, AI systems, and product engineering domains. - Ability to translate complex technical challenges into scalable architectural patterns. - Excellent communication and stakeholder management skills, with the ability to influence technical direction across multiple disciplines. Nice to Have - Experience with AI agents, orchestration frameworks, or agent-based architectures. - Experience designing AI platforms or enterprise-scale AI systems. - Knowledge of workflow orchestration, tool integration, memory, and context management concepts. - Experience with observability, reliability engineering, and operational excellence practices. - Experience with cloud platforms and modern platform engineering environments. - Familiarity with emerging AI technologies and engineering automation practices. Responsibilities - Define and evolve the architecture of the AI platform. - Develop reusable architectural patterns for agent orchestration, workflow execution, tool integration, memory, context management, and platform services. - Establish engineering standards for APIs, distributed systems, observability, testing, deployment, documentation, and operational excellence. - Drive architectural decisions across Product Engineering, Platform Engineering, Data, Security, and Product teams. - Lead the evolution of the Agentic Software Development Lifecycle (ASDLC), promoting increased adoption of automation and autonomous agents within engineering processes. - Identify reusable platform capabilities that reduce duplication and accelerate delivery. - Review technical designs and provide architectural guidance on strategic initiatives. - Balance long-term platform evolution with pragmatic product delivery needs. - Evaluate emerging technologies and frameworks, adopting them where they provide measurable value. - Coach senior engineers through design reviews, technical guidance, and architectural leadership. - Champion practices that improve developer experience, reliability, scalability, and operational efficiency.