Senior Principal Technical Program Manager - Agent Infrastructure

Working at Atlassian Atlassians can choose where they work – whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity. The Opportunity & Strategic Context We are looking for a Senior Principal Technical Program Manager (P70) to lead the strategy, architecture-informed execution, and ecosystem scaling of our core Conversational AI & Agent Platforms . In this role, you will drive the evolution of foundational conversational interfaces, distributed agent execution runtimes, extensible skill ecosystems, contextual memory architectures, and policy-driven model routing. As an industry leader in enterprise collaboration, we are raising the bar: treating our AI platform infrastructure not merely as backend microservices, but as high-leverage Platform Products with first-class state-of-the-art capabilities and developer experience, robust API contracts, resilient operational SLOs, and sound unit economics. Drive Platform-as-a-Product Strategy: Champion a "Platform as a Product" mindset and define & lead platform evolution, developer experience, API standards, SDKs, runtime guardrails, and adoption pathways for internal squads and external partners building on top of our AI platform. Orchestrate Agent & AI Architecture: Partner with Principal Engineers, Architects, and Product Leads to deliver multi-quarter roadmaps for agent execution loops, semantic memory, tool/skill orchestration, and policy-driven model routing. Lead Large-Scale Platform Evolutions: Direct complex, multi-team platform migrations and convergence efforts with zero disruption to end-user experiences. Champion Operational Excellence & SLOs: Establish world-class availability, latency budgets, graceful degradation patterns, and end-to-end observability across high-throughput, low-latency AI serving infrastructure. Govern AI Economics & Efficiency: Contribute to the technical levers of AI unit economics—driving inference cost-per-query optimizations, caching strategies, and capacity planning without compromising quality or safety. Ensure Enterprise Trust & Compliance: Lead the technical readiness for multi-region data residency, enterprise privacy controls, and AI safety guardrails. Influence Across Leadership: Align cross-functional teams and executive leadership through structured operating rhythms, clear decision frameworks & artifacts, and transparent communication. Elevate the TPM Craft: Mentor and coach technical program managers, setting the benchmark for platform thinking, architectural depth, and execution excellence across the organization. Must-Have Qualifications 12+ years of experience in Technical Program Management, Platform Product Management, or Distributed Systems Engineering, with 4+ years focused on AI/ML platforms or high-scale developer platforms . Deep Generative AI & Agentic Fluency: Strong working understanding of modern LLM architectures, agent execution loops, context-window management, Retrieval-Augmented Generation (RAG), embeddings, and semantic memory systems. Platform Product Mindset: Demonstrated success treating backend APIs, developer tools, and shared runtimes as products measured by adoption, developer velocity, and platform health. Systems Architecture Depth: Ability to dive into technical concepts such as sequence diagrams, distributed caching, rate limiting, and API gateways alongside senior engineering leadership. Executive Presence & High-Ambiguity Leadership: Proven ability to turn broad, undefined problem spaces into clear technical roadmaps, structured RFCs, and decision frameworks for senior leadership. AI Cost Governance: Familiarity and ideally, experience modeling inference unit economics, cost-per-request reduction, and multi-model routing trade-offs. Desired / Preferred Qualifications Experience with standardized agent-tool protocols (e.g., Model Context Protocol - MCP, OpenAPI-based tool ecosystems). Familiarity with offline LLM evaluation harnesses, synthetic benchmarking, and red-teaming pipelines. Background in multi-cloud, distributed deployment strategies (AWS, GCP, Azure) and hybrid inferencing infrastructure. Working knowledge of enterprise data compliance standards (GDPR, EU AI Act, FedRAMP). Background in Software Engineering: Prior experience writing code, designing REST/gRPC/GraphQL APIs, or contributing directly to open-source developer ecosystems. Benefits & Perks Atlassian offers a wide range of perks and benefits designed to support you, your family and to help you engage with your local community. Our offerings include health and wellbeing resources, paid volunteer days, and so much more. To learn more, visit go.atlassian.com/perksandbenefits . About Atlassian At Atlassian, we're motivated by a common goal: to unleash the potential of every team. Our software products help teams all over the planet and our solutions are designed for all types of work. Team collaboration through our tools makes what may be impossible alone, possible together. We believe that the unique contributions of all Atlassians create our success. To ensure that our products and culture continue to incorporate everyone's perspectives and experience, we never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines. To provide you the best experience, we can support with accommodations or adjustments at any stage of the recruitment process. Simply inform our Recruitment team during your conversation with them. To learn more about our culture and hiring process, visit go.atlassian.com/crh . In line with local law, identity verification (which may include use of biometric data) is a condition of employment with Atlassian for employment fraud purposes.