RESPEC
Principle Agilist
Washington, DC, United States
Sponsorship not specifiedDetected 181 days ago
CI/CDJiraLeadershipMentoringRenewable Energy
About the role
- If you're someone who sees problems as opportunities, you'll thrive here.
- RESPEC is 100% employee-owned, which means we take ownership of every challenge.
- Since 1969, we've tackled complex challenges in energy transition, infrastructure resilience, digital transformation, and sustainability.
Responsibilities
- Lead all SAFe® transformation activities across OCI.
- Empower high-performing Agile teams to drive value and sustain organizational change.
- Lead the stand-up of Agile teams from traditional structures.
- Provide "at-the-elbow" support to ensure employees successfully leverage SAFe® best practices.
- Coordinate and maintain the CDP, including Continuous Exploration, Integration, Deployment, and Release on Demand.
Requirements
- Certified SAFe® Practice Consultant (SPC) (Required).
Skills
- Big challenges need bold thinkers.
- Here, your ideas drive real solutions.
- Ensure that velocity and impact are visible to senior VHA leaders.
- Mastery of Jira Align and Jira for enterprise-level Agile tracking.
Compensation
- Salary depends on experience and expertise.
- Compensation includes a comprehensive fringe-benefits package.
- 401(k) & ESOP (with company match up to 4%)
- Professional Development and Training
- Employee Assistance Program
Benefits
- RESPEC is a 100% employee-owned company and employees are eligible for participation in the Employee Stock Ownership Plan (ESOP) after a qualifying period.
- Featured benefits include:
- Flexible Work Schedules
- Paid Parental Leave
- Tuition Reimbursement
- Medical/Dental/Vision Insurance Plans
Equal opportunity
- Employer, including veterans and individuals with disabilities.
- All your information will be kept confidential according to EEO guidelines.
- Equal Opportunity Employer, including veterans and individuals with disabilities.
This listing is sourced directly from RESPEC's careers page and normalized into a canonical job model.