Manage, mentor, and develop a team of Release Coordinators, providing regular coaching, feedback, and performance guidance.
Conduct performance reviews and support team members in setting and achieving professional development goals.
Assign and balance workload across the team based on release scope, complexity, and individual capacity.
Foster a team culture of accountability, continuous learning, and effective use of AI tools in day-to-day workflows.
Participate in hiring and onboarding of new Release Coordinators.
Oversee and guide the team in working closely with development, testing, and deployment teams to plan release activities, using AI-powered project tools to track dependencies and surface scheduling conflicts proactively.
Develop and maintain release schedules with the aid of AI-assisted risk modeling to anticipate bottlenecks and downstream impacts.
Coordinate with stakeholders to ensure alignment on release timelines.
Engage with clients on a regular basis to review release readiness.
Facilitate communication between development, QA, operations, and client-facing teams throughout the release lifecycle.
Use AI writing tools to draft and refine release notes, stakeholder updates, and post-release summaries with clarity and consistency.
Provide regular updates to stakeholders on release progress, using AI-generated digests where appropriate to keep communications timely and concise.
Serve as an escalation point for client and cross-team communications when releases are at risk.
Identify potential risks and issues that may impact end users, leveraging AI-assisted analysis of historical release data and open tickets to flag patterns early.
Guide the team in developing contingency plans and mitigating risks before they reach production.
Ensure that all release documentation is accurate, up-to-date, and accessible
using AI tools to assist with drafting, reviewing, and maintaining configuration run lists and release checklists.
Apply AI-assisted summarization to consolidate complex release notes into clear, client-appropriate communications.
Collaborate with QA teams to ensure adequate testing is conducted before releases reach production.
Promote the use of AI-assisted test case generation to broaden team coverage, particularly for regression and edge-case scenarios.
Schedule and oversee testing activities, including user acceptance testing (UAT) and regression testing.
Ensure the team maintains a thorough understanding of how current clients use Nymbus products, including files, settings, queries, and back-office configurations.
Guide coordinators in understanding expected feature behavior based on acceptance criteria and using AI tools to cross-reference behavior against documented requirements.
Ensure issues found during testing are clearly documented, properly dispositioned, and escalated appropriately.
Coach team members on recognizing and accurately assessing issue severity.
Encourage creative, scenario-based thinking when designing test cases, including conditions derived from real client-reported issues.
Coordinate deployment activities with infrastructure teams, ensuring AI-powered monitoring tools are in place prior to go-live.
Monitor the deployment process to ensure it follows the planned schedule; confirm rollback procedures are ready if needed.
Participate in upgrade events, using AI-assisted runbooks and checklists to reduce manual error.
Monitor post-release stability using AI-powered observability and alerting tools to detect anomalies quickly.
Oversee the team's coordination and resolution of issues that arise post-release.
Ensure urgent and high-priority issues are escalated promptly to mitigate end-user risk.
Collect and synthesize feedback from clients, stakeholders, and teams for continuous improvement
using AI tools to identify themes and recurring patterns across releases.
Coordinate with the infrastructure team to manage and maintain consistency across environments.
Ensure environments are refreshed with current data and configuration is consistent with production.
Use AI-assisted environment comparison tools where available to catch configuration drift early.
Identify opportunities for process improvement in the release management lifecycle, including adoption of new AI-powered tooling.
Implement best practices and incorporate lessons learned from previous releases.
Stay current on emerging AI tools relevant to release management, QA, and DevOps workflows, and guide the team in adopting them effectively.
Provide training and support to the release coordination team and cross-functional partners, including guidance on effective use of AI tools within release workflows.
Foster a culture of collaboration, continuous learning, and communication to enhance the efficiency of the release process.
Requirements
Bachelor's degree in a related field
Knowledge of customer service techniques and standards
2+ years of people management or team lead experience
Proven organizational, analytical, and communication skills
Several years of banking experience preferred, specializing in Deposits, Loans, GL, or Back Office Operations
Working knowledge of Google Suite, Microsoft Office (Word, Excel, PowerPoint), and modern collaboration platforms
Working knowledge of JIRA and Confluence
Familiarity with AI productivity tools (e.g., AI writing assistants, automated test generation, AI-powered monitoring/observability platforms); ability and willingness to adopt new tools as they emerge
Strong verbal and written communication skills, including the ability to write clearly with or without AI assistance
Effective public presentation skills
Diligent time management and analytical skills
Maintain flexibility in schedule to allow for occasional travel and ability to work evening and/or weekend hours
Perform all other related duties as required or assigned
Process
and detail-oriented with a continuous improvement mindset
Benefits
Annual Cash Bonus and Equity Options commensurate with the role level and experience