Job Description
An opening exists for a Head – AI Risk Solutions to join the Artificial Intelligence (AI) vertical, focused on AI-driven Risk Management. This is a senior level opening based out of Lucknow, offered on a full-time basis.
The ideal candidate holds M.Sc (Data Science) and brings roughly 16 years of hands-on exposure to ai-driven risk management. Day-to-day, the work draws heavily on Deep Learning, Python, Natural Language Processing, Model Deployment (MLOps), and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 52.1-119.0 LPA, in line with market standards for senior level roles within artificial intelligence (ai).
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
References may be requested closer to the offer stage rather than at the start of the process. The role alternates between independent deep work and short coordination huddles with stakeholders across functions. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. The package is structured with a fixed component, performance bonus, and standard health coverage.
Most days include at least one review checkpoint where progress is discussed against the plan for the week. Interested candidates should be prepared to walk through relevant past work during the interview process.
The next logical step from this position is a senior or lead-track role within the same function. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work.
Internal job postings are open to employees who've completed a minimum tenure in their current role. 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. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. The organisation has historically promoted from within for a majority of its senior and lead openings.
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here.
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. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
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.Sc (Data Science) and brings roughly 16 years of hands-on exposure to ai-driven risk management. Day-to-day, the work draws heavily on Deep Learning, Python, Natural Language Processing, Model Deployment (MLOps), and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 52.1-119.0 LPA, in line with market standards for senior level roles within artificial intelligence (ai).
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
References may be requested closer to the offer stage rather than at the start of the process. The role alternates between independent deep work and short coordination huddles with stakeholders across functions. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. The package is structured with a fixed component, performance bonus, and standard health coverage.
Most days include at least one review checkpoint where progress is discussed against the plan for the week. Interested candidates should be prepared to walk through relevant past work during the interview process.
The next logical step from this position is a senior or lead-track role within the same function. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work.
Internal job postings are open to employees who've completed a minimum tenure in their current role. 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. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. The organisation has historically promoted from within for a majority of its senior and lead openings.
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here.
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. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
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.