Job Description
**Chief AI Security Officer** | Hyderabad | Leadership - Full-time | INR 21.1-84.5 LPA
**About the role:**
- Position within AI Security & Privacy, under the Artificial Intelligence (AI) vertical
- Level: senior level
- Reports to the functional head for AI Security & Privacy
**What you'll do:**
- Handle core ai security & privacy activities on a day-to-day basis
- Use AI Security 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:**
- AI Security
- Model Deployment (MLOps)
- Neural Network Architectures
- Data Preprocessing
- Natural Language Processing
- Python
- Privacy
- TensorFlow/PyTorch
- Ph.D (AI)
- 8+ years of relevant experience
**Good to know:**
- Interested candidates should be prepared to walk through relevant past work during the interview process. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
- Compensation includes standard statutory benefits along with performance-linked variable pay. References may be requested closer to the offer stage rather than at the start of the process. Relocation assistance may be extended for candidates moving from a different city, subject to approval.
- The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.
- A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
- The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. 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. 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. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done.
- 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. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
- High performers in this role typically move into a broader ownership scope within 18-24 months. The package is structured with a fixed component, performance bonus, and standard health coverage. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy.
- Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. There is a defined internal mobility path for people who want to specialise deeper or move into people management. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
**About the role:**
- Position within AI Security & Privacy, under the Artificial Intelligence (AI) vertical
- Level: senior level
- Reports to the functional head for AI Security & Privacy
**What you'll do:**
- Handle core ai security & privacy activities on a day-to-day basis
- Use AI Security 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:**
- AI Security
- Model Deployment (MLOps)
- Neural Network Architectures
- Data Preprocessing
- Natural Language Processing
- Python
- Privacy
- TensorFlow/PyTorch
- Ph.D (AI)
- 8+ years of relevant experience
**Good to know:**
- Interested candidates should be prepared to walk through relevant past work during the interview process. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
- Compensation includes standard statutory benefits along with performance-linked variable pay. References may be requested closer to the offer stage rather than at the start of the process. Relocation assistance may be extended for candidates moving from a different city, subject to approval.
- The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.
- A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
- The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. 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. 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. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done.
- 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. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
- High performers in this role typically move into a broader ownership scope within 18-24 months. The package is structured with a fixed component, performance bonus, and standard health coverage. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy.
- Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. There is a defined internal mobility path for people who want to specialise deeper or move into people management. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.