Technical Program Manager - Engineering Operations
G
G-PSaaS
United States: California or Philadelphia, PennsylvaniaFull-TimeMiddle
Salary not disclosed
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Job Details
- Experience
- 5+ years
- Required Skills
- AWSPythonArtificial IntelligenceJavascriptJQLGitHub
Requirements
- 5+ years in Engineering Operations (EngOps), Program Management, or a similar data-heavy engineering role.
- Expert-level administration skills with Jira Cloud.
- Power user proficiency with Jellyfish.
- Deep understanding of Agile metrics and Engineering Investment categories.
- Strong knowledge of DORA metrics (Deployment Frequency, Lead Time for Changes, Change Failure Rate, and Time to Restore Service).
- Advanced proficiency in Jira Automation.
- Advanced proficiency in JQL.
- Foundational knowledge of the SDLC process.
- Foundational knowledge of Scrum methodology.
- Foundational knowledge of SAFe methodologies.
- Comfortable leveraging AI agents for data analysis and scripting tasks.
- Comfortable leveraging LLMs for data analysis and scripting tasks.
- Ability to write basic Python or JavaScript for API integrations (preferred).
- Experience with GitHub (preferred).
- Experience with AWS (preferred).
Responsibilities
- Design, build and maintain complex workflows, permission schemes, and automation rules in Jira Cloud at scale.
- Map Jira "Signals" to Jellyfish allocation buckets, ensuring data reflects true "Investment Distribution".
- Standardize issue types and field usage across 20+ squads to ensure Jellyfish insights are statistically valid.
- Use Atlassian Intelligence to translate plain-English requests into complex JQL for instant reporting.
- Leverage Jellyfish AI Impact to measure how AI coding assistants (Copilot, Cursor) are shifting "Time to Deliver" and code quality.
- Integrate AI Agents to handle "ticket hygiene" such as flagging stale issues, summarizing comment threads, and triaging requests.
- Use LLMs (Claude/ChatGPT) to synthesize monthly Jellyfish data into executive-level narratives.
- Monitor Cycle Time, Lead Time, and Deployment Frequency (DORA & Flow Metrics) to identify systemic bottlenecks and improvement opportunities.
- Partner with Finance to use Jellyfish data for R&D tax credit reporting and labor capitalization.
- Work with stakeholders on triaging and aligning requirements in conjunction with tool administrators.
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