Job Description
**Chief AI Ethics Officer** | Hyderabad | Hybrid | INR 12.1-62.3 LPA
**About the role:**
- Position within AI Governance & Compliance, under the Artificial Intelligence (AI) vertical
- Level: senior level
- Reports to the functional head for AI Governance & Compliance
**What you'll do:**
- Handle core ai governance & compliance activities on a day-to-day basis
- Use Data Preprocessing regularly as part of core deliverables
- Work closely with adjacent teams to align priorities
- Track progress against agreed timelines and escalate issues proactively
**What you'll need:**
- Data Preprocessing
- Model Deployment (MLOps)
- AI Governance
- Deep Learning
- Neural Network Architectures
- Compliance
- M.Tech (AI/ML)
- 14+ years of relevant experience
**Good to know:**
- High performers in this role typically move into a broader ownership scope within 18-24 months. 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. The next logical step from this position is a senior or lead-track role within the same function.
- There is a defined internal mobility path for people who want to specialise deeper or move into people management. 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. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy.
- Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work.
- Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
- Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Relocation assistance may be extended for candidates moving from a different city, subject to approval. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
- The organisation has historically promoted from within for a majority of its senior and lead openings. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done.
- The package is structured with a fixed component, performance bonus, and standard health coverage. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
- Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments.
- Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. References may be requested closer to the offer stage rather than at the start of the process.
**About the role:**
- Position within AI Governance & Compliance, under the Artificial Intelligence (AI) vertical
- Level: senior level
- Reports to the functional head for AI Governance & Compliance
**What you'll do:**
- Handle core ai governance & compliance activities on a day-to-day basis
- Use Data Preprocessing regularly as part of core deliverables
- Work closely with adjacent teams to align priorities
- Track progress against agreed timelines and escalate issues proactively
**What you'll need:**
- Data Preprocessing
- Model Deployment (MLOps)
- AI Governance
- Deep Learning
- Neural Network Architectures
- Compliance
- M.Tech (AI/ML)
- 14+ years of relevant experience
**Good to know:**
- High performers in this role typically move into a broader ownership scope within 18-24 months. 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. The next logical step from this position is a senior or lead-track role within the same function.
- There is a defined internal mobility path for people who want to specialise deeper or move into people management. 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. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy.
- Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work.
- Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
- Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Relocation assistance may be extended for candidates moving from a different city, subject to approval. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
- The organisation has historically promoted from within for a majority of its senior and lead openings. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done.
- The package is structured with a fixed component, performance bonus, and standard health coverage. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
- Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments.
- Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. References may be requested closer to the offer stage rather than at the start of the process.