Job Description
Artificial Intelligence (AI) is looking for an experienced AI Privacy Consultant to take ownership of the AI Security & Privacy charter at a mid level. This is a role for someone who has already operated at scale and is comfortable setting direction rather than simply following one.
The successful candidate will bring approximately 4 years of progressively senior experience, holding M.Tech (AI/ML), with a demonstrated track record across TensorFlow/PyTorch, Statistical Modelling, Neural Network Architectures, AI Security, Machine Learning. Beyond individual capability, this role expects the person to mentor junior team members and represent the function in cross-departmental discussions.
Reporting relationships will be defined based on the final scope agreed at offer stage, and the role is based out of Bhubaneswar on a contract arrangement. Compensation is benchmarked at INR 12.1-41.0 LPA, reflecting the seniority and scope of the position.
Success in this role will be measured less by task completion and more by the quality of judgement applied to ambiguous, high-stakes situations within ai security & privacy.
The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. The organisation has historically promoted from within for a majority of its senior and lead openings. The next logical step from this position is a senior or lead-track role within the same function.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. There is a defined internal mobility path for people who want to specialise deeper or move into people management. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
Learning and certification support is available for tools and frameworks directly relevant to the role. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Relocation assistance may be extended for candidates moving from a different city, subject to approval.
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. Compensation includes standard statutory benefits along with performance-linked variable pay. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here.
References may be requested closer to the offer stage rather than at the start of the process. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments.
Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
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 package is structured with a fixed component, performance bonus, and standard health coverage.
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. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
The successful candidate will bring approximately 4 years of progressively senior experience, holding M.Tech (AI/ML), with a demonstrated track record across TensorFlow/PyTorch, Statistical Modelling, Neural Network Architectures, AI Security, Machine Learning. Beyond individual capability, this role expects the person to mentor junior team members and represent the function in cross-departmental discussions.
Reporting relationships will be defined based on the final scope agreed at offer stage, and the role is based out of Bhubaneswar on a contract arrangement. Compensation is benchmarked at INR 12.1-41.0 LPA, reflecting the seniority and scope of the position.
Success in this role will be measured less by task completion and more by the quality of judgement applied to ambiguous, high-stakes situations within ai security & privacy.
The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. The organisation has historically promoted from within for a majority of its senior and lead openings. The next logical step from this position is a senior or lead-track role within the same function.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. There is a defined internal mobility path for people who want to specialise deeper or move into people management. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
Learning and certification support is available for tools and frameworks directly relevant to the role. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Relocation assistance may be extended for candidates moving from a different city, subject to approval.
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. Compensation includes standard statutory benefits along with performance-linked variable pay. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here.
References may be requested closer to the offer stage rather than at the start of the process. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments.
Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
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 package is structured with a fixed component, performance bonus, and standard health coverage.
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. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.