Job Description
We are looking to onboard an Executive Director – AI Risk & Compliance to strengthen our AI Governance & Compliance function within Artificial Intelligence (AI). This is a senior level opening based out of Chandigarh, offered on a hybrid basis.
The ideal candidate holds M.Tech (AI/ML) and brings roughly 8 years of hands-on exposure to ai governance & compliance. Day-to-day, the work draws heavily on Deep Learning, Model Deployment (MLOps), AI Governance, Machine Learning, and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 15.6-48.4 LPA, in line with market standards for senior level roles within artificial intelligence (ai).
Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
References may be requested closer to the offer stage rather than at the start of the process. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments.
Most days include at least one review checkpoint where progress is discussed against the plan for the week. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. There is a defined internal mobility path for people who want to specialise deeper or move into people management.
There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
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. Interested candidates should be prepared to walk through relevant past work during the interview process. Compensation includes standard statutory benefits along with performance-linked variable pay.
Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Learning and certification support is available for tools and frameworks directly relevant to the role.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. Relocation assistance may be extended for candidates moving from a different city, subject to approval.
The next logical step from this position is a senior or lead-track role within the same function. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions.
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
The organisation has historically promoted from within for a majority of its senior and lead openings. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
This is a good fit for someone who wants real ownership rather than a purely execution-only role.
The ideal candidate holds M.Tech (AI/ML) and brings roughly 8 years of hands-on exposure to ai governance & compliance. Day-to-day, the work draws heavily on Deep Learning, Model Deployment (MLOps), AI Governance, Machine Learning, and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 15.6-48.4 LPA, in line with market standards for senior level roles within artificial intelligence (ai).
Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
References may be requested closer to the offer stage rather than at the start of the process. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments.
Most days include at least one review checkpoint where progress is discussed against the plan for the week. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. There is a defined internal mobility path for people who want to specialise deeper or move into people management.
There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
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. Interested candidates should be prepared to walk through relevant past work during the interview process. Compensation includes standard statutory benefits along with performance-linked variable pay.
Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Learning and certification support is available for tools and frameworks directly relevant to the role.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. Relocation assistance may be extended for candidates moving from a different city, subject to approval.
The next logical step from this position is a senior or lead-track role within the same function. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions.
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
The organisation has historically promoted from within for a majority of its senior and lead openings. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
This is a good fit for someone who wants real ownership rather than a purely execution-only role.