Job Description
**AI Risk Advisory Engineer** | Remote (Pan India) | Full-time | INR 17.1-40.7 LPA
**About the role:**
- Position within AI-driven Risk Management, under the Artificial Intelligence (AI) vertical
- Level: mid level
- Reports to the functional head for AI-driven Risk Management
**What you'll do:**
- Handle core ai-driven risk management activities on a day-to-day basis
- Use Statistical Modelling regularly as part of core deliverables
- Work closely with adjacent teams to align priorities
- Track progress against agreed timelines and escalate issues proactively
**What you'll need:**
- Statistical Modelling
- Natural Language Processing
- driven Risk Management
- Python
- Data Preprocessing
- M.Sc (Data Science)
- 3+ years of relevant experience
**Good to know:**
- New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Internal job postings are open to employees who've completed a minimum tenure in their current role. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.
- The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
- A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability.
- 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.
- Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
- The package is structured with a fixed component, performance bonus, and standard health coverage. 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.
- Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
- There is a defined internal mobility path for people who want to specialise deeper or move into people management. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here.
- High performers in this role typically move into a broader ownership scope within 18-24 months. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
- References may be requested closer to the offer stage rather than at the start of the process. 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. Interested candidates should be prepared to walk through relevant past work during the interview process.
- Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
**About the role:**
- Position within AI-driven Risk Management, under the Artificial Intelligence (AI) vertical
- Level: mid level
- Reports to the functional head for AI-driven Risk Management
**What you'll do:**
- Handle core ai-driven risk management activities on a day-to-day basis
- Use Statistical Modelling regularly as part of core deliverables
- Work closely with adjacent teams to align priorities
- Track progress against agreed timelines and escalate issues proactively
**What you'll need:**
- Statistical Modelling
- Natural Language Processing
- driven Risk Management
- Python
- Data Preprocessing
- M.Sc (Data Science)
- 3+ years of relevant experience
**Good to know:**
- New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Internal job postings are open to employees who've completed a minimum tenure in their current role. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.
- The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
- A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability.
- 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.
- Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
- The package is structured with a fixed component, performance bonus, and standard health coverage. 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.
- Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
- There is a defined internal mobility path for people who want to specialise deeper or move into people management. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here.
- High performers in this role typically move into a broader ownership scope within 18-24 months. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
- References may be requested closer to the offer stage rather than at the start of the process. 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. Interested candidates should be prepared to walk through relevant past work during the interview process.
- Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.