Job Description
Position: AI Risk Analytics Specialist
Function: AI-driven Risk Management
Industry: Artificial Intelligence (AI)
Grade: mid level
Location: Lucknow
Employment Type: Full-time
Compensation: INR 22.4-56.4 LPA
The organisation invites applications for the above-referenced position. The incumbent shall be responsible for discharging duties associated with ai-driven risk management, in accordance with the standards and processes laid down by Artificial Intelligence (AI).
Minimum Qualification: M.Tech (AI/ML)
Minimum Experience: 4 years
Core Competencies Required: TensorFlow/PyTorch, Deep Learning, Data Preprocessing, Cloud Platforms (AWS/GCP/Azure), Machine Learning, driven Risk Management, Python
Further Information:
Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. 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. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. The organisation has historically promoted from within for a majority of its senior and lead openings. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. 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. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. There is a defined internal mobility path for people who want to specialise deeper or move into people management. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. Internal job postings are open to employees who've completed a minimum tenure in their current role. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. The next logical step from this position is a senior or lead-track role within the same function. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. High performers in this role typically move into a broader ownership scope within 18-24 months. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
Function: AI-driven Risk Management
Industry: Artificial Intelligence (AI)
Grade: mid level
Location: Lucknow
Employment Type: Full-time
Compensation: INR 22.4-56.4 LPA
The organisation invites applications for the above-referenced position. The incumbent shall be responsible for discharging duties associated with ai-driven risk management, in accordance with the standards and processes laid down by Artificial Intelligence (AI).
Minimum Qualification: M.Tech (AI/ML)
Minimum Experience: 4 years
Core Competencies Required: TensorFlow/PyTorch, Deep Learning, Data Preprocessing, Cloud Platforms (AWS/GCP/Azure), Machine Learning, driven Risk Management, Python
Further Information:
Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. 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. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. The organisation has historically promoted from within for a majority of its senior and lead openings. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. 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. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. There is a defined internal mobility path for people who want to specialise deeper or move into people management. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. Internal job postings are open to employees who've completed a minimum tenure in their current role. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. The next logical step from this position is a senior or lead-track role within the same function. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. High performers in this role typically move into a broader ownership scope within 18-24 months. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.