Job Description
This position calls for an Enterprise AI Security Architect who can take ownership of core responsibilities within our AI for Cybersecurity team. This is a senior level opening based out of Mumbai, offered on a full-time basis.
The ideal candidate holds M.Tech (Machine Learning) and brings roughly 8 years of hands-on exposure to ai for cybersecurity. Day-to-day, the work draws heavily on Computer Vision/NLP Basics, Cloud Platforms (AWS/GCP), Python, Deep Learning, and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 30.5-58.6 LPA, in line with market standards for senior level roles within machine learning.
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
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. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. There is a defined internal mobility path for people who want to specialise deeper or move into people management. 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. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy.
Interested candidates should be prepared to walk through relevant past work during the interview process. Internal job postings are open to employees who've completed a minimum tenure in their current role. 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. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Learning and certification support is available for tools and frameworks directly relevant to the role. The organisation has historically promoted from within for a majority of its senior and lead openings.
References may be requested closer to the offer stage rather than at the start of the process. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work.
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.
We value consistency and follow-through more than flashy credentials - if that matches how you work, apply in.
The ideal candidate holds M.Tech (Machine Learning) and brings roughly 8 years of hands-on exposure to ai for cybersecurity. Day-to-day, the work draws heavily on Computer Vision/NLP Basics, Cloud Platforms (AWS/GCP), Python, Deep Learning, and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 30.5-58.6 LPA, in line with market standards for senior level roles within machine learning.
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
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. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. There is a defined internal mobility path for people who want to specialise deeper or move into people management. 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. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy.
Interested candidates should be prepared to walk through relevant past work during the interview process. Internal job postings are open to employees who've completed a minimum tenure in their current role. 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. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Learning and certification support is available for tools and frameworks directly relevant to the role. The organisation has historically promoted from within for a majority of its senior and lead openings.
References may be requested closer to the offer stage rather than at the start of the process. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work.
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.
We value consistency and follow-through more than flashy credentials - if that matches how you work, apply in.