Agile Project Manager

• Own end-to-end delivery of AI-focused software development projects, from planning through execution and to deployment.
• Translate business objectives and technical insights into actionable requirements, features, and user stories.
• Emphasis on the ability to break down the requirements into user demo-able stories (vertical slicing rather than technical or horizontal slicing).
• Collaborate with clients & team (data scientists, ML engineers, developers, testers, devops) to define project scope, prioritize features, manage backlogs, create schedules, resource allocation, risks & mitigation, defect management, and monitor progress.
• Assess team capabilities and guide effort estimation with a strong understanding of AI project complexities.
• Act as the central point of communication between stakeholders including clients, internal teams, and senior leadership.
• Ensure adherence to AI development of best practices and software quality standards. Guide and track automation testing along with product development.
• Ensure agile & development processes are followed – documentation, process across DSLC / SDLC, agile ceremonies like backlog grooming & planning, scrum, weekly demos, retrospectives, etc.
• Manage change requests, evaluate their impact, and adjust scope, timelines, and resources accordingly.
• Monitor progress, track milestones, and ensure timely delivery of high-quality AI solutions.
• Oversee multiple AI projects simultaneously, ensuring alignment with strategic goals and client expectations.
• Weekly updates on progress, schedules, and KPIs/metrics to senior leadership on all projects.

Minimum Qualifications and Experience:

• Bachelor’s degree in computer science, Information Technology, or a related field.
• 5–7 years of total experience, with 3–5 years in agile project management roles using scrum or scrumban, preferably in AI, Data Science, or software product environments.

Required Expertise:

• Strong understanding of Agile methodologies like Scrum & Kanban; Scrum Master certification is a plus.
• Experience managing AI/ML projects including Generative AI, Computer Vision, NLP, IoT, etc.
• Familiarity with tools like GitHub, Jira, or similar platforms for tracking development activities.
• Solid grasp of software effort estimation, especially for AI and data-driven projects.
• Ability to understand technical concepts in AI and communicate effectively with both technical and non-technical stakeholders.
• Experience working with Developers, Data Scientist, AI/ML/Gen AI Engineers, Automation Testing, Devops, CloudOps & Deployment teams for end-to-end experience in DSLC & SDLC.