Engineering Operations Manager

The Engineering Operations Manager owns the tools, processes, and integrations that support the Product Engineering and Technical Program Management organization. The role is shifting from tool administration toward engineering productivity and operations: reducing friction in engineering workflows, building the integrations and AI-assisted SDLC tooling that make that possible, and serving as the technical lead for junior team members working in that space.

The ideal candidate is a fully competent, independent technical contributor who can also mentor less experienced colleagues. They are comfortable learning new technologies, building integrations, evaluating AI-assisted output critically, and driving adoption of better ways of working across diverse teams.

• →Tooling Platform Strategy & Automation - Own the roadmap and architecture for Jira, Confluence, Jellyfish, and future engineering tools. Push configuration and administration work toward automation and self-service rather than performing it manually. Where manual administration remains necessary, delegate it to the junior team member or automate it — it should not be the primary use of this role's time.
• →Integrations & AI SDLC - Build and maintain integrations between engineering systems using REST APIs, webhooks, and scripting. Direct and evaluate AI-assisted SDLC work, including prompt and spec writing, output evaluation, and connector or tool development. Serve as technical lead and review point for the Jr Developer, Engineering Operations role on this work.
• →Executive Reporting - Turn Jira and Jellyfish data into reliable metrics and executive-ready reporting. Maintain the roadmap-to-delivery mapping (Initiatives, Features, confidence ratings, SME verification) as an ongoing discipline rather than a one-time exercise.
• →Program & Release Support - Support program and release management with tooling, data, and process guidance across the SDLC.
• →Process Standardization - Define and enforce consistent tool usage patterns across engineering, product, and TPgM teams to improve collaboration and efficiency.
• →Engineering Productivity & Cross-Functional Partnership - Partner with engineering and product leadership to reduce friction in day-to-day workflows, treating engineers as the customer of this team's tools and processes rather than as subjects of administration.
• →Technical Mentorship - Provide technical direction, code and configuration review, and skill development for junior team members working on integrations and AI SDLC.

• Bachelor’s degree in Computer Science or related field, or equivalent experience.
• 4+ years of experience in engineering operations, tooling, integrations, or process management.
• Working proficiency in Python and REST API integration patterns: auth flows, pagination, rate limits, retry logic.
• Git and PR-based workflow.
• Practical experience using an LLM as a working tool, including where it fails.
• Strong written communication spanning executive narrative and technical writing (specs, prompts, evaluation criteria).
• Demonstrated ability to mentor or provide technical guidance to less experienced team members.
• Strong analytical and problem-solving skills with high attention to detail.
• Self-starter, comfortable operating without an established right answer.

• Experience administering Atlassian tools (Jira, Confluence) — now context for the role, not its core.
• SQL for reading data: joins, aggregation, filtering.
• Experience with MCP or connector development, agentic patterns, and tool or skill design.
• Familiarity with Jellyfish or comparable engineering intelligence platforms.
• Experience with Agile methodologies and software development life cycle processes.
• Secrets and credential hygiene across systems.