Job Description
The organisation is seeking a qualified AI Risk Strategy Manager to support ongoing initiatives in AI-driven Risk Management. This is a senior level opening based out of Kolkata, offered on a leadership - full-time basis.
The ideal candidate holds M.Tech (AI/ML) and brings roughly 10 years of hands-on exposure to ai-driven risk management. Day-to-day, the work draws heavily on driven Risk Management, Deep Learning, Computer Vision, Data Preprocessing, and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 10.3-36.6 LPA, in line with market standards for senior level roles within artificial intelligence (ai).
Interested candidates should be prepared to walk through relevant past work during the interview process. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. Relocation assistance may be extended for candidates moving from a different city, subject to approval. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work.
Most days include at least one review checkpoint where progress is discussed against the plan for the week. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability.
Internal job postings are open to employees who've completed a minimum tenure in their current role. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.
Learning and certification support is available for tools and frameworks directly relevant to the role. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. Compensation includes standard statutory benefits along with performance-linked variable pay.
The role alternates between independent deep work and short coordination huddles with stakeholders across functions. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. There is a defined internal mobility path for people who want to specialise deeper or move into people management.
The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. 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.
High performers in this role typically move into a broader ownership scope within 18-24 months. References may be requested closer to the offer stage rather than at the start of the process. The package is structured with a fixed component, performance bonus, and standard health coverage.
Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. The next logical step from this position is a senior or lead-track role within the same function. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
If your background aligns with the above and you're looking for your next step in AI-driven Risk Management, we'd like to hear from you.
The ideal candidate holds M.Tech (AI/ML) and brings roughly 10 years of hands-on exposure to ai-driven risk management. Day-to-day, the work draws heavily on driven Risk Management, Deep Learning, Computer Vision, Data Preprocessing, and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 10.3-36.6 LPA, in line with market standards for senior level roles within artificial intelligence (ai).
Interested candidates should be prepared to walk through relevant past work during the interview process. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. Relocation assistance may be extended for candidates moving from a different city, subject to approval. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work.
Most days include at least one review checkpoint where progress is discussed against the plan for the week. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability.
Internal job postings are open to employees who've completed a minimum tenure in their current role. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.
Learning and certification support is available for tools and frameworks directly relevant to the role. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. Compensation includes standard statutory benefits along with performance-linked variable pay.
The role alternates between independent deep work and short coordination huddles with stakeholders across functions. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. There is a defined internal mobility path for people who want to specialise deeper or move into people management.
The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. 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.
High performers in this role typically move into a broader ownership scope within 18-24 months. References may be requested closer to the offer stage rather than at the start of the process. The package is structured with a fixed component, performance bonus, and standard health coverage.
Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. The next logical step from this position is a senior or lead-track role within the same function. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
If your background aligns with the above and you're looking for your next step in AI-driven Risk Management, we'd like to hear from you.