Microsoft SR TECHNICAL PROGRAM MANAGER 

Taiwan, Taoyuan City 

469883770

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Required Qualifications

• Bachelor's Degree AND 4+ years experience in engineering, product/technical program management, data analysis, or product development
  • OR equivalent experience.
• 2+ years of experience managing cross-functional and/or cross-team projects.

Preferred Qualifications

• Experience building platform services on Azure or another major cloud using AI technologies. Examples include Azure OpenAI Service, Azure AI Studio, Azure Machine Learning, Azure Functions, or Kubernetes.
• Experience with data analytics technologies, including Azure Data Explorer, SQL, data extraction, transformation, and loading (ETL), machine learning (ML), Power BI, and semantic data models such as Microsoft Fabric OneLake.
• Hands on familiarity with AI copilots and agents, retrieval grounded generation, secure connectors and tools, and evaluation for groundedness, quality, and safety.
• Ability to lead through ambiguity while partnering across organizations, with a demonstrated ability to come up to speed quickly on new technical domains.
• Experience using data to drive prioritization and measure progress, including objectives and key results (OKRs), key performance indicators (KPIs), experimentation, and telemetry.
• Experience managing multiple concurrent projects in a fast paced environment with global stakeholders.
• Proven collaboration and communication skills, verbal and written, including executive ready storytelling and clear decision and risk communication.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:Microsoft will accept applications for the role until October 14, 2025.

Platform and Services:

• Build, ship, and operate common platform capabilities. Examples include prompt orchestration and versioning, retrieval grounded generation adapters, secure tool and skill catalogs, model routing, Responsible AI guardrails, evaluation, observability, and telemetry. Define service level objectives (SLOs), service level indicators (SLIs), runbooks, incident response, and balance quality, latency, and cost.

AI Applications and Workflow Transformation:

• Deliver AI copilots, agents, and automations for Finance workflows, including financial planning and analysis, close and consolidation, revenue and margin analysis, spend governance, and compliance and controls. Partner with data platform teams to ensure trustworthy data and lineage across Microsoft Fabric OneLake, Azure Data Explorer (Kusto), SQL, and semantic models.

Security, Privacy, and Compliance:

• Implement Responsible AI controls such as risk assessment, red teaming, personal data and toxicity filtering, role based access, auditability, and records retention. Ensure compliance by design and privacy preserving patterns for all services and experiences.

Program Leadership and Execution:

• Lead cross organization planning and delivery across multiple workstreams. Run the rhythm of business, manage dependencies, report status, and drive risk and decision forums. Capture Epics and Features with acceptance goals and success metrics. Engineering leads author user stories and technical designs.

Measurement and Adoption:

• Instrument telemetry and experiments, including A/B testing and feature flags. Track adoption, groundedness and accuracy, time to completion, and cost per task. Use insights to iterate and improve.

Enablement and Change Management:

• Prepare launches, training, documentation, and communications. Drive behavior change in Finance and scale awareness and uptake of platform services.

Collaboration and Technology Scouting:

• Engage Finance stakeholders, subject matter experts, engineering and product teams, and industry partners. Evaluate emerging technologies and bring actionable recommendations into product solutions.

Continous Improvement and Growth Mindset: