Principal Technical Program Manager
- Compensation
- Not disclosed
- Location
- Seattle, WA, US
- Work setup
- Remote
- Seniority
- Principal
- Employment
- Not specified
- Experience
- 3+ years
- Category
- Project management
- Posted
Skills
Must have
- 10+ years on software teams as a Development Manager or TPM, including 3+ years on ML, AI platform or large-scale infrastructure programs.
- Working knowledge of LLM architecture, inference optimization, serving frameworks and GPU infrastructure economics.
- Experience with multi-vendor GPU or inference-provider strategies and AI cost management
- Experience with benchmarking and model evaluation methods.
- TPMs are not expected to write or read code, but must understand system flows, block architectures and APIs.
- A track record of running end-to-end, complex, cross-org technical programs with significant budget.
- Strategic thinking and ability to turn business objectives into technical programs with measurable results.
- Strong leadership, organizational and communication skills, including influencing senior engineers and executives without direct authority.
Full description
Overview
We are seeking a Principal Technical Program Manager to drive technical strategy, infrastructure planning, and cross-functional execution across our LLM inference platform.
In this role, you will lead end-to-end programs spanning GPU capacity planning, inference optimization, model migrations, and cost-per-token efficiency, while building standardized benchmarking frameworks and governance policies to evaluate, select, and scale open-weight models safely across the organization. The scope will evolve as the platform and industry mature, so success requires strong technical judgment, structured execution, and comfort operating in ambiguity.
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.
Responsibilities
- Set a long-term strategy and roadmap for the open-weight LLM inference platform. Base it on business goals, customer needs, barriers to adoption and industry trends, and build it with stakeholders across Engineering, Product, Security and Finance.
- Turn business goals into ranked technical problems, such as cost per token, latency, throughput, reliability and model coverage.
- Define and run programs for GPU capacity planning, inference optimization, model migrations, high availability and performance.
- Build a consistent way to benchmark and evaluate open-weight models, covering serving performance, quality and cost.
- Give leadership and teams data-backed recommendations for model selection.
- Work with Security, Legal and Compliance on the policies and security requirements that let teams adopt open-weight and OSS models safely.
- Partner with and influence engineers, ML engineers and architects to settle trade-offs and keep programs moving.
- Own programs end to end, from initiation through forecasting, budgeting and scheduling to delivery, including inference cost models.
- Manage complex dependencies across the company and with external partners, such as cloud and GPU providers.
Compensation
At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. We follow consistent hiring practices and account for each candidate's skills, knowledge, and experience when setting base pay within the range.
Please visit go.atlassian.com/payzones for more information on which locations are included in each of our geographic pay zones. However, please confirm the zone for your specific location with your recruiter.