Job Description
Artificial Intelligence (AI) is looking for an experienced VP – AI Policy & Regulatory Affairs to take ownership of the AI Ethics & Governance charter at a senior level. This is a role for someone who has already operated at scale and is comfortable setting direction rather than simply following one.
The successful candidate will bring approximately 8 years of progressively senior experience, holding M.Tech (AI/ML), with a demonstrated track record across Neural Network Architectures, Governance, AI Ethics, Model Deployment (MLOps), TensorFlow/PyTorch. Beyond individual capability, this role expects the person to mentor junior team members and represent the function in cross-departmental discussions.
Reporting relationships will be defined based on the final scope agreed at offer stage, and the role is based out of Kolkata on a full-time arrangement. Compensation is benchmarked at INR 10.7-68.3 LPA, reflecting the seniority and scope of the position.
Success in this role will be measured less by task completion and more by the quality of judgement applied to ambiguous, high-stakes situations within ai ethics & governance.
New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
Compensation includes standard statutory benefits along with performance-linked variable pay. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
References may be requested closer to the offer stage rather than at the start of the process. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
Mornings are usually spent on planning and status reviews, while the rest of the day is given over to hands-on delivery and problem-solving. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.
Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. The package is structured with a fixed component, performance bonus, and standard health coverage.
In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. Internal job postings are open to employees who've completed a minimum tenure in their current role.
The role alternates between independent deep work and short coordination huddles with stakeholders across functions. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
The organisation has historically promoted from within for a majority of its senior and lead openings. Learning and certification support is available for tools and frameworks directly relevant to the role. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
The successful candidate will bring approximately 8 years of progressively senior experience, holding M.Tech (AI/ML), with a demonstrated track record across Neural Network Architectures, Governance, AI Ethics, Model Deployment (MLOps), TensorFlow/PyTorch. Beyond individual capability, this role expects the person to mentor junior team members and represent the function in cross-departmental discussions.
Reporting relationships will be defined based on the final scope agreed at offer stage, and the role is based out of Kolkata on a full-time arrangement. Compensation is benchmarked at INR 10.7-68.3 LPA, reflecting the seniority and scope of the position.
Success in this role will be measured less by task completion and more by the quality of judgement applied to ambiguous, high-stakes situations within ai ethics & governance.
New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
Compensation includes standard statutory benefits along with performance-linked variable pay. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
References may be requested closer to the offer stage rather than at the start of the process. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
Mornings are usually spent on planning and status reviews, while the rest of the day is given over to hands-on delivery and problem-solving. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.
Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. The package is structured with a fixed component, performance bonus, and standard health coverage.
In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. Internal job postings are open to employees who've completed a minimum tenure in their current role.
The role alternates between independent deep work and short coordination huddles with stakeholders across functions. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
The organisation has historically promoted from within for a majority of its senior and lead openings. Learning and certification support is available for tools and frameworks directly relevant to the role. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.