Job Description
AI Policy & Ethics Lead | Gurugram | INR 18.6-29.6 LPA
AI Ethics & Governance role, mid level, full-time.
Need: B.Tech (CS/AI), 7+ yrs.
Core skills: Data Preprocessing, Natural Language Processing, Neural Network Architectures, Governance, AI Ethics.
If this fits your profile in ai ethics & governance, apply now.
The organisation has historically promoted from within for a majority of its senior and lead openings. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.
Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. The next logical step from this position is a senior or lead-track role within the same function. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy.
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. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability.
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments.
Compensation includes standard statutory benefits along with performance-linked variable pay. Interested candidates should be prepared to walk through relevant past work during the interview process. Internal job postings are open to employees who've completed a minimum tenure in their current role.
There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.
Learning and certification support is available for tools and frameworks directly relevant to the role. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
The package is structured with a fixed component, performance bonus, and standard health coverage. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. References may be requested closer to the offer stage rather than at the start of the process. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work.
AI Ethics & Governance role, mid level, full-time.
Need: B.Tech (CS/AI), 7+ yrs.
Core skills: Data Preprocessing, Natural Language Processing, Neural Network Architectures, Governance, AI Ethics.
If this fits your profile in ai ethics & governance, apply now.
The organisation has historically promoted from within for a majority of its senior and lead openings. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.
Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. The next logical step from this position is a senior or lead-track role within the same function. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy.
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. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability.
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments.
Compensation includes standard statutory benefits along with performance-linked variable pay. Interested candidates should be prepared to walk through relevant past work during the interview process. Internal job postings are open to employees who've completed a minimum tenure in their current role.
There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.
Learning and certification support is available for tools and frameworks directly relevant to the role. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
The package is structured with a fixed component, performance bonus, and standard health coverage. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. References may be requested closer to the offer stage rather than at the start of the process. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work.