Job Description
We are looking to onboard an AI Learning Quality Manager to strengthen our AI in Education function within EdTech. This is a mid level opening based out of Hybrid - Bengaluru, offered on a full-time basis.
The ideal candidate holds MBA (EdTech/Marketing) and brings roughly 5 years of hands-on exposure to ai in education. Day-to-day, the work draws heavily on Content Strategy (EdTech), AI in Education, LMS Platforms, A/B Testing (EdTech), and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 16.2-24.6 LPA, in line with market standards for mid level roles within edtech.
Interested candidates should be prepared to walk through relevant past work during the interview process. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
The package is structured with a fixed component, performance bonus, and standard health coverage. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. There is a defined internal mobility path for people who want to specialise deeper or move into people management. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done.
Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.
This is a good fit for someone who wants real ownership rather than a purely execution-only role.
The ideal candidate holds MBA (EdTech/Marketing) and brings roughly 5 years of hands-on exposure to ai in education. Day-to-day, the work draws heavily on Content Strategy (EdTech), AI in Education, LMS Platforms, A/B Testing (EdTech), and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 16.2-24.6 LPA, in line with market standards for mid level roles within edtech.
Interested candidates should be prepared to walk through relevant past work during the interview process. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
The package is structured with a fixed component, performance bonus, and standard health coverage. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. There is a defined internal mobility path for people who want to specialise deeper or move into people management. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done.
Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.
This is a good fit for someone who wants real ownership rather than a purely execution-only role.