Job Description
This position calls for an AI Risk Analyst – Junior who can take ownership of core responsibilities within our AI-driven Risk Management team. This is a junior level opening based out of Hybrid - Pune, offered on a full-time (wfh) basis.
The ideal candidate holds M.Tech (AI/ML) and brings roughly 2 years of hands-on exposure to ai-driven risk management. Day-to-day, the work draws heavily on Model Deployment (MLOps), driven Risk Management, Cloud Platforms (AWS/GCP/Azure), Natural Language Processing, and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 13.0-22.7 LPA, in line with market standards for junior level roles within artificial intelligence (ai).
Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. 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. Compensation includes standard statutory benefits along with performance-linked variable pay.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. 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. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
The organisation has historically promoted from within for a majority of its senior and lead openings. Learning and certification support is available for tools and frameworks directly relevant to the role. High performers in this role typically move into a broader ownership scope within 18-24 months.
No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. 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. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
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 2 years of hands-on exposure to ai-driven risk management. Day-to-day, the work draws heavily on Model Deployment (MLOps), driven Risk Management, Cloud Platforms (AWS/GCP/Azure), Natural Language Processing, and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 13.0-22.7 LPA, in line with market standards for junior level roles within artificial intelligence (ai).
Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. 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. Compensation includes standard statutory benefits along with performance-linked variable pay.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. 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. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
The organisation has historically promoted from within for a majority of its senior and lead openings. Learning and certification support is available for tools and frameworks directly relevant to the role. High performers in this role typically move into a broader ownership scope within 18-24 months.
No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. 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. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
This role offers a genuine opportunity to build depth in AI-driven Risk Management while working alongside an experienced team.