Job Description
## AI Governance Manager
**Department:** AI Governance & Compliance | **Industry:** Artificial Intelligence (AI)
**Location:** Chennai | **Job Type:** Full-time | **CTC:** INR 9.9-43.9 LPA
### Role Overview
We are looking to onboard an AI Governance Manager to strengthen our AI Governance & Compliance function within Artificial Intelligence (AI). The role is positioned at the mid level and reports into the broader AI Governance & Compliance charter.
### Key Responsibilities
- Own end-to-end delivery of tasks related to ai governance & compliance.
- Apply working knowledge of Machine Learning and Statistical Modelling to daily execution.
- Coordinate with cross-functional stakeholders within Artificial Intelligence (AI).
- Maintain documentation and reporting as required by the team lead.
- Flag risks and blockers early rather than at review checkpoints.
### Requirements
- M.Sc (Data Science) or equivalent qualification.
- 3 years of relevant experience (mid level).
- Working proficiency in: Machine Learning, Statistical Modelling, Cloud Platforms (AWS/GCP/Azure), Compliance, AI Governance.
### Additional Notes
The organisation has historically promoted from within for a majority of its senior and lead openings. Interested candidates should be prepared to walk through relevant past work during the interview process. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. Internal job postings are open to employees who've completed a minimum tenure in their current role. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. 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. The next logical step from this position is a senior or lead-track role within the same function. Compensation includes standard statutory benefits along with performance-linked variable pay. There is a defined internal mobility path for people who want to specialise deeper or move into people management. The package is structured with a fixed component, performance bonus, and standard health coverage. Learning and certification support is available for tools and frameworks directly relevant to the role. 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. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. 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. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. References may be requested closer to the offer stage rather than at the start of the process.
**Department:** AI Governance & Compliance | **Industry:** Artificial Intelligence (AI)
**Location:** Chennai | **Job Type:** Full-time | **CTC:** INR 9.9-43.9 LPA
### Role Overview
We are looking to onboard an AI Governance Manager to strengthen our AI Governance & Compliance function within Artificial Intelligence (AI). The role is positioned at the mid level and reports into the broader AI Governance & Compliance charter.
### Key Responsibilities
- Own end-to-end delivery of tasks related to ai governance & compliance.
- Apply working knowledge of Machine Learning and Statistical Modelling to daily execution.
- Coordinate with cross-functional stakeholders within Artificial Intelligence (AI).
- Maintain documentation and reporting as required by the team lead.
- Flag risks and blockers early rather than at review checkpoints.
### Requirements
- M.Sc (Data Science) or equivalent qualification.
- 3 years of relevant experience (mid level).
- Working proficiency in: Machine Learning, Statistical Modelling, Cloud Platforms (AWS/GCP/Azure), Compliance, AI Governance.
### Additional Notes
The organisation has historically promoted from within for a majority of its senior and lead openings. Interested candidates should be prepared to walk through relevant past work during the interview process. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. Internal job postings are open to employees who've completed a minimum tenure in their current role. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. 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. The next logical step from this position is a senior or lead-track role within the same function. Compensation includes standard statutory benefits along with performance-linked variable pay. There is a defined internal mobility path for people who want to specialise deeper or move into people management. The package is structured with a fixed component, performance bonus, and standard health coverage. Learning and certification support is available for tools and frameworks directly relevant to the role. 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. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. 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. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. References may be requested closer to the offer stage rather than at the start of the process.