Job Description
The organisation is seeking a qualified AI Risk Monitoring Engineer to support ongoing initiatives in AI-driven Risk Management. This is a mid level opening based out of Lucknow, offered on a hybrid basis.
The ideal candidate holds M.Tech (AI/ML) and brings roughly 6 years of hands-on exposure to ai-driven risk management. Day-to-day, the work draws heavily on Model Deployment (MLOps), Natural Language Processing, Deep Learning, driven Risk Management, and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 18.2-31.1 LPA, in line with market standards for mid level roles within artificial intelligence (ai).
Learning and certification support is available for tools and frameworks directly relevant to the role. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Relocation assistance may be extended for candidates moving from a different city, subject to approval.
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. The package is structured with a fixed component, performance bonus, and standard health coverage.
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.
The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. 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. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. References may be requested closer to the offer stage rather than at the start of the process.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. Compensation includes standard statutory benefits along with performance-linked variable pay. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
This role offers a genuine opportunity to build depth in AI-driven Risk Management 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-driven risk management. Day-to-day, the work draws heavily on Model Deployment (MLOps), Natural Language Processing, Deep Learning, driven Risk Management, and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 18.2-31.1 LPA, in line with market standards for mid level roles within artificial intelligence (ai).
Learning and certification support is available for tools and frameworks directly relevant to the role. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Relocation assistance may be extended for candidates moving from a different city, subject to approval.
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. The package is structured with a fixed component, performance bonus, and standard health coverage.
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.
The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. 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. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. References may be requested closer to the offer stage rather than at the start of the process.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. Compensation includes standard statutory benefits along with performance-linked variable pay. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
This role offers a genuine opportunity to build depth in AI-driven Risk Management while working alongside an experienced team.