Job Description
Join us as an AI Risk Technology Specialist and help us push AI-driven Risk Management forward within Artificial Intelligence (AI).
You'll be working out of Noida (full-time (wfh)), and honestly, the day-to-day is going to revolve around driven Risk Management and Statistical Modelling. We're not looking for someone who just ticks boxes - we want someone who actually cares about ai-driven risk management.
On paper, we'd expect M.Tech (AI/ML) and somewhere around 3 years of experience, but we're just as interested in how you think as in what's on your resume.
Pay-wise, we're offering INR 17.7-39.2 LPA - fair for the mid level band and open to discussion based on what you bring.
New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. 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. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
High performers in this role typically move into a broader ownership scope within 18-24 months. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. The organisation has historically promoted from within for a majority of its senior and lead openings.
Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Compensation includes standard statutory benefits along with performance-linked variable pay. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
Relocation assistance may be extended for candidates moving from a different city, subject to approval. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. Interested candidates should be prepared to walk through relevant past work during the interview process.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. The package is structured with a fixed component, performance bonus, and standard health coverage. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy.
You'll be working out of Noida (full-time (wfh)), and honestly, the day-to-day is going to revolve around driven Risk Management and Statistical Modelling. We're not looking for someone who just ticks boxes - we want someone who actually cares about ai-driven risk management.
On paper, we'd expect M.Tech (AI/ML) and somewhere around 3 years of experience, but we're just as interested in how you think as in what's on your resume.
Pay-wise, we're offering INR 17.7-39.2 LPA - fair for the mid level band and open to discussion based on what you bring.
New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. 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. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
High performers in this role typically move into a broader ownership scope within 18-24 months. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. The organisation has historically promoted from within for a majority of its senior and lead openings.
Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Compensation includes standard statutory benefits along with performance-linked variable pay. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
Relocation assistance may be extended for candidates moving from a different city, subject to approval. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. Interested candidates should be prepared to walk through relevant past work during the interview process.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. The package is structured with a fixed component, performance bonus, and standard health coverage. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy.