UI/UX Designer
- India
نُشرت أول أمس
عن الوظيفة
Experience: 5-10 years of relevant experience in technical project/program management; exact years were not specified in the source.
Location: Pune, India
Job Summary
Own and drive enterprise AI projects in an Agile environment, coordinating engineering, QA, infrastructure, operations, product, and customer stakeholders. The role requires enough technical depth to understand AI platform/product offerings, CI/CD, infrastructure, deployment, release, and operational processes without being a hands-on specialist in every area.
Key Responsibilities
Drive projects end-to-end in an Agile manner, including requirement gathering, sprint planning, estimation, sequencing, dependency management, execution, and delivery.
Ability to co-work with Agentic AI model, Optimizing processes agnatically [agentic optimizing engineering. SAS, Jira, salesforce optimization, streamline the process
Coordinate enterprise AI deployments across engineering, QA, infrastructure, operations, and support teams.
Understand the flow from engineering preparation and QA through infrastructure handover, operational testing, deployment, release, and upgrade management.
Work closely with customer-side product managers to understand priorities and translate them into actionable engineering work.
Understand the organization’s AI product offerings and features sufficiently to plan and drive solutions effectively.
Coordinate developers, QA, DevOps/SRE, infrastructure, ML, and other technical team members.
Manage workload, capacity, dependencies, blockers, and parallel workstreams across the team.
Drive daily stand-ups, sprint execution, status tracking, and project governance.
Track project progress, quality, bugs, technical debt, risks, and dependencies through appropriate dashboards and reports.
Prepare and present weekly status reports and project updates to senior stakeholders and customers.
Support the onboarding of new team members and set clear expectations regarding roles and responsibilities.
Track team-member performance and maintain relevant inputs for performance reviews.
Maintain strong communication with customers and internal stakeholders throughout the project lifecycle.
Must be available for on-call support as needed
Ability to collaborate effectively with Agentic AI models
Capability to optimize repetitive processes and workflows using agentic/autonomous engineering approaches
Required Skills
Strong understanding of Agile project management practices.
Experience with requirement gathering, sprint planning, story-point estimation, sequencing, dependencies, and sprint execution.
Working understanding of CI/CD and enterprise deployment processes.
Understanding infrastructure, Kubernetes, and related technical concepts at a functional level.
Awareness of SRE/operations practices, release and upgrade management, incident management, problem management, and change management.
Understanding platform readiness and production operations.
Strong project dashboards, reporting, and stakeholder-management capabilities.
Ability to understand the responsibilities and technical blockers of different engineering roles.
Soft Skills
Excellent customer and stakeholder communication.
Strong coordination and leadership skills.
Ability to conduct technical discussions and communicate priorities clearly.
Strong ownership, organization, and problem-solving skills.
Location: Pune, India
Job Summary
Own and drive enterprise AI projects in an Agile environment, coordinating engineering, QA, infrastructure, operations, product, and customer stakeholders. The role requires enough technical depth to understand AI platform/product offerings, CI/CD, infrastructure, deployment, release, and operational processes without being a hands-on specialist in every area.
Key Responsibilities
Drive projects end-to-end in an Agile manner, including requirement gathering, sprint planning, estimation, sequencing, dependency management, execution, and delivery.
Ability to co-work with Agentic AI model, Optimizing processes agnatically [agentic optimizing engineering. SAS, Jira, salesforce optimization, streamline the process
Coordinate enterprise AI deployments across engineering, QA, infrastructure, operations, and support teams.
Understand the flow from engineering preparation and QA through infrastructure handover, operational testing, deployment, release, and upgrade management.
Work closely with customer-side product managers to understand priorities and translate them into actionable engineering work.
Understand the organization’s AI product offerings and features sufficiently to plan and drive solutions effectively.
Coordinate developers, QA, DevOps/SRE, infrastructure, ML, and other technical team members.
Manage workload, capacity, dependencies, blockers, and parallel workstreams across the team.
Drive daily stand-ups, sprint execution, status tracking, and project governance.
Track project progress, quality, bugs, technical debt, risks, and dependencies through appropriate dashboards and reports.
Prepare and present weekly status reports and project updates to senior stakeholders and customers.
Support the onboarding of new team members and set clear expectations regarding roles and responsibilities.
Track team-member performance and maintain relevant inputs for performance reviews.
Maintain strong communication with customers and internal stakeholders throughout the project lifecycle.
Must be available for on-call support as needed
Ability to collaborate effectively with Agentic AI models
Capability to optimize repetitive processes and workflows using agentic/autonomous engineering approaches
Required Skills
Strong understanding of Agile project management practices.
Experience with requirement gathering, sprint planning, story-point estimation, sequencing, dependencies, and sprint execution.
Working understanding of CI/CD and enterprise deployment processes.
Understanding infrastructure, Kubernetes, and related technical concepts at a functional level.
Awareness of SRE/operations practices, release and upgrade management, incident management, problem management, and change management.
Understanding platform readiness and production operations.
Strong project dashboards, reporting, and stakeholder-management capabilities.
Ability to understand the responsibilities and technical blockers of different engineering roles.
Soft Skills
Excellent customer and stakeholder communication.
Strong coordination and leadership skills.
Ability to conduct technical discussions and communicate priorities clearly.
Strong ownership, organization, and problem-solving skills.