Principal Technical Program Manager- Agent Quality and API Governance

Atlassian•Mountain View, CA

15d•$169,569 - $266,725•Hybrid

About The Position

Atlassian is seeking a Principal Technical Program Manager to drive technical strategy and cross-functional execution across agent integration, quality, and API governance platform layers. The role leads programs and platforms that help agents connect reliably to first- and third-party tools, establish ways to measure and improve agent quality, and govern agent and automation traffic through rate limits, quotas, API standards, and runtime safeguards. The scope will evolve as the platform and industry mature, requiring strong technical judgment, structured execution, and comfort operating in ambiguity. Atlassians may work from an office, from home, or a combination of the two. Atlassian can hire in any country where it has a legal entity. The role covers tool-calling interfaces and integration patterns; authentication, identity, permissions, and credential management; onboarding and lifecycle management for tools and automated actions; quality measurement, evaluation benchmarks, and observability; API rate limits, quotas, resilience, standards, versioning, compatibility, deprecation, and monetization; and cross-functional roadmaps, ownership, milestones, and technical decision-making.

Requirements

8–10+ years of experience in Technical Program Management, Platform Product Management, software engineering, or a related technical discipline.
Experience delivering API platforms, distributed backend systems, developer ecosystems, automation platforms, or AI/ML integrations.
Strong understanding of API architecture, distributed rate limiting, quotas, concurrency controls, resilience patterns, and API lifecycle governance.
Working knowledge of agent execution, function calling, tool binding, action schemas, and integration protocols.
Understanding of agent quality measurement, including task success, accuracy, representative test cases, and human- or model-assisted evaluation.
Ability to engage deeply and partner with senior engineers on technical reviews, RFCs, sequence diagrams, and failure-mode analysis.
Proven ability to create structure, clarify ownership, and deliver outcomes in evolving and ambiguous platform domains.

Nice To Haves

Experience with standardized AI agents, agentic workflows, and agent-tool protocols such as Model Context Protocol (MCP) and OpenAPI-based tool ecosystems.
Familiarity with offline LLM evaluation harnesses, synthetic benchmarking, and red-teaming pipelines.
Experience with developer-facing integration ecosystems, app marketplaces, workflow engines, or automation platforms.
Familiarity with agent observability, distributed tracing, OpenTelemetry, and quality or evaluation tooling.
Background in multi-cloud distributed deployment strategies (AWS, GCP, Azure) and hybrid inferencing infrastructure.
Experience defining platform metrics that connect technical health, adoption, reliability, and user outcomes.

Responsibilities

Drive standardized tool-calling interfaces, action schemas, and integration patterns across internal and external ecosystems.
Partner with Security and Identity teams on authentication, token exchange, permission scopes, tenant isolation, and credential management.
Improve onboarding and lifecycle management for teams and partners adding tools, skills, and automated actions.
Define practical measures for agent accuracy, task completion, tool selection, groundedness, safety, and user experience.
Establish representative test sets, evaluation benchmarks, golden scenarios, and regression practices for prompt, model, tool, and workflow changes.
Partner with engineering teams on agent traces and telemetry to diagnose multi-step execution, tool failures, latency, and quality issues.
Lead rate limiting, tenant quotas, concurrency controls, and traffic-shaping strategies across agent APIs and automation triggers.
Establish safeguards against runaway loops and downstream failures, including timeouts, retries, backoff, circuit breakers, and graceful degradation.
Drive API standards, versioning, backward compatibility, breaking-change management, and deprecation practices.
Drive API monetization capabilities, including standardization of API units and metering integration across experiences and interfaces.
Turn ambiguous, multi-team problems into clear roadmaps, milestones, ownership models, and technical decision documents.
Facilitate trade-offs such as synchronous versus asynchronous tool execution, live versus offline quality signals, and global versus tenant-scoped controls.