Techolution - Release Manager - Azure/DevOps

<p><p>Location : Hyderabad(Hybrid).<br/><br/> Work Timings : 2:00 PM 11:00 PM IST.<br/><br/> No of Openings : 1.</p><p><br/><b>Key Responsibilities :</b><br/><br/></p><p>- Lead and evolve the AI product release strategy, with a focus on automation, predictability, and scalability.<br/><br/></p><p>- Develop frictionless release systems that minimize manual handoffs and support frequent deployments.<br/><br/></p><p>- Partner with cross-functional teams (Product, Engineering, QA, MLOps) to align release planning with product goals.<br/><br/></p><p>- Establish and enforce release governance, quality checks, and approval workflows.<br/><br/></p><p>- Maintain a centralized release calendar, including planning, coordination, and execution of releases.<br/><br/></p><p>- Identify and remove bottlenecks across the release lifecycle.<br/><br/></p><p>- Oversee release readiness reviews, go/no-go decisions, and post-release retrospectives.<br/><br/></p><p>- Define and monitor key release health metrics (e.g., lead time, failure rates, rollback incidents).<br/><br/></p><p>- Advocate for continuous improvement, scalable practices, and automation-first principles in release management.</p><p><br/><b>Required Skills and Qualifications :</b><br/><br/></p><p>- 3+ years of experience in Release Management within a tech or product-based environment.<br/><br/></p><p>- Proven experience in managing end-to-end release cycles for complex digital products preferably AI, data, or platform-based.<br/><br/></p><p>- Strong knowledge of Agile/Scrum methodologies and experience managing cross-functional Agile teams.<br/><br/></p><p>- Demonstrated ability to optimize and scale release processes, with a focus on automation and reducing manual intervention.<br/><br/></p><p>- Experience working with release calendars, governance workflows, and stakeholder communication in fast-paced environments.<br/><br/></p><p>- Familiarity with basic AI/ML development workflows (e.g., model versioning, testing, and deployment cycles) is a plus but deep technical ML knowledge is not required.<br/><br/></p><p>- Exposure to tools like Jira, Azure DevOps, Confluence, or other project/release management platforms.<br/><br/></p><p>- Excellent communication and coordination skills, with a track record of aligning multiple teams and functions toward shared release goals.</p><br/></p> (ref:hirist.tech)