Job Description
Looking for a Principal Ethical AI Advisor who's genuinely interested in AI Ethics & Governance and wants to make an impact from day one.
You'll be working out of Nagpur (full-time), and honestly, the day-to-day is going to revolve around TensorFlow/PyTorch and Cloud Platforms (AWS/GCP/Azure). We're not looking for someone who just ticks boxes - we want someone who actually cares about ai ethics & governance.
On paper, we'd expect M.Sc (Data Science) and somewhere around 11 years of experience, but we're just as interested in how you think as in what's on your resume.
Pay-wise, we're offering INR 33.7-55.6 LPA - fair for the senior level band and open to discussion based on what you bring.
The package is structured with a fixed component, performance bonus, and standard health coverage. Relocation assistance may be extended for candidates moving from a different city, subject to approval.
The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. High performers in this role typically move into a broader ownership scope within 18-24 months. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. Learning and certification support is available for tools and frameworks directly relevant to the role.
Compensation includes standard statutory benefits along with performance-linked variable pay. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
Most days include at least one review checkpoint where progress is discussed against the plan for the week. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. 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 team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions.
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy.
Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. 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.
You'll be working out of Nagpur (full-time), and honestly, the day-to-day is going to revolve around TensorFlow/PyTorch and Cloud Platforms (AWS/GCP/Azure). We're not looking for someone who just ticks boxes - we want someone who actually cares about ai ethics & governance.
On paper, we'd expect M.Sc (Data Science) and somewhere around 11 years of experience, but we're just as interested in how you think as in what's on your resume.
Pay-wise, we're offering INR 33.7-55.6 LPA - fair for the senior level band and open to discussion based on what you bring.
The package is structured with a fixed component, performance bonus, and standard health coverage. Relocation assistance may be extended for candidates moving from a different city, subject to approval.
The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. High performers in this role typically move into a broader ownership scope within 18-24 months. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. Learning and certification support is available for tools and frameworks directly relevant to the role.
Compensation includes standard statutory benefits along with performance-linked variable pay. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
Most days include at least one review checkpoint where progress is discussed against the plan for the week. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. 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 team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions.
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy.
Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. 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.