Job Description
We are looking to onboard an Enterprise AI Compliance Architect to strengthen our AI Policy & Compliance function within Machine Learning. This is a senior level opening based out of Mumbai, offered on a leadership - full-time basis.
The ideal candidate holds Ph.D (ML/AI) and brings roughly 11 years of hands-on exposure to ai policy & compliance. Day-to-day, the work draws heavily on AI Policy, Machine Learning Algorithms, Feature Engineering, Deep Learning, and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 9.4-38.2 LPA, in line with market standards for senior level roles within machine learning.
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. The organisation has historically promoted from within for a majority of its senior and lead openings. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.
The role alternates between independent deep work and short coordination huddles with stakeholders across functions. Interested candidates should be prepared to walk through relevant past work during the interview process.
References may be requested closer to the offer stage rather than at the start of the process. The next logical step from this position is a senior or lead-track role within the same function. High performers in this role typically move into a broader ownership scope within 18-24 months.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. 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.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Relocation assistance may be extended for candidates moving from a different city, subject to approval.
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. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. Learning and certification support is available for tools and frameworks directly relevant to the role. 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. Compensation includes standard statutory benefits along with performance-linked variable pay. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
This role offers a genuine opportunity to build depth in AI Policy & Compliance while working alongside an experienced team.
The ideal candidate holds Ph.D (ML/AI) and brings roughly 11 years of hands-on exposure to ai policy & compliance. Day-to-day, the work draws heavily on AI Policy, Machine Learning Algorithms, Feature Engineering, Deep Learning, and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 9.4-38.2 LPA, in line with market standards for senior level roles within machine learning.
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. The organisation has historically promoted from within for a majority of its senior and lead openings. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.
The role alternates between independent deep work and short coordination huddles with stakeholders across functions. Interested candidates should be prepared to walk through relevant past work during the interview process.
References may be requested closer to the offer stage rather than at the start of the process. The next logical step from this position is a senior or lead-track role within the same function. High performers in this role typically move into a broader ownership scope within 18-24 months.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. 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.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Relocation assistance may be extended for candidates moving from a different city, subject to approval.
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. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. Learning and certification support is available for tools and frameworks directly relevant to the role. 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. Compensation includes standard statutory benefits along with performance-linked variable pay. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
This role offers a genuine opportunity to build depth in AI Policy & Compliance while working alongside an experienced team.