Job Description
The organisation is seeking a qualified AI Governance Coordinator to support ongoing initiatives in AI Ethics & Governance. This is a mid level opening based out of Gurugram, offered on a contract basis.
The ideal candidate holds M.Tech (AI/ML) and brings roughly 6 years of hands-on exposure to ai ethics & governance. Day-to-day, the work draws heavily on TensorFlow/PyTorch, AI Ethics, Statistical Modelling, Cloud Platforms (AWS/GCP/Azure), and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 7.0-18.5 LPA, in line with market standards for mid level roles within artificial intelligence (ai).
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions.
Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
Most days include at least one review checkpoint where progress is discussed against the plan for the week. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.
New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work.
In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. 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. Learning and certification support is available for tools and frameworks directly relevant to the role. 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.
Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. The package is structured with a fixed component, performance bonus, and standard health coverage. 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. References may be requested closer to the offer stage rather than at the start of the process.
There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. High performers in this role typically move into a broader ownership scope within 18-24 months.
This role offers a genuine opportunity to build depth in AI Ethics & Governance while working alongside an experienced team.
The ideal candidate holds M.Tech (AI/ML) and brings roughly 6 years of hands-on exposure to ai ethics & governance. Day-to-day, the work draws heavily on TensorFlow/PyTorch, AI Ethics, Statistical Modelling, Cloud Platforms (AWS/GCP/Azure), and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 7.0-18.5 LPA, in line with market standards for mid level roles within artificial intelligence (ai).
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions.
Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
Most days include at least one review checkpoint where progress is discussed against the plan for the week. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.
New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work.
In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. 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. Learning and certification support is available for tools and frameworks directly relevant to the role. 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.
Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. The package is structured with a fixed component, performance bonus, and standard health coverage. 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. References may be requested closer to the offer stage rather than at the start of the process.
There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. High performers in this role typically move into a broader ownership scope within 18-24 months.
This role offers a genuine opportunity to build depth in AI Ethics & Governance while working alongside an experienced team.