Job Description
## AI Security Technology Strategist
**Department:** AI for Cybersecurity | **Industry:** Machine Learning
**Location:** Hybrid - Pune | **Job Type:** Full-time | **CTC:** INR 53.8-79.2 LPA
### Role Overview
This position calls for an AI Security Technology Strategist who can take ownership of core responsibilities within our AI for Cybersecurity team. The role is positioned at the senior level and reports into the broader AI for Cybersecurity charter.
### Key Responsibilities
- Own end-to-end delivery of tasks related to ai for cybersecurity.
- Apply working knowledge of Statistical Modelling and Data Preprocessing to daily execution.
- Coordinate with cross-functional stakeholders within Machine Learning.
- Maintain documentation and reporting as required by the team lead.
- Flag risks and blockers early rather than at review checkpoints.
### Requirements
- M.Tech (Machine Learning) or equivalent qualification.
- 10 years of relevant experience (senior level).
- Working proficiency in: Statistical Modelling, Data Preprocessing, Machine Learning Algorithms, AI for Cybersecurity, Python, Deep Learning, Cloud Platforms (AWS/GCP).
### Additional Notes
Interested candidates should be prepared to walk through relevant past work during the interview process. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Compensation includes standard statutory benefits along with performance-linked variable pay. The role alternates between independent deep work and short coordination huddles with stakeholders across functions. Relocation assistance may be extended for candidates moving from a different city, subject to approval. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. 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. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. There is a defined internal mobility path for people who want to specialise deeper or move into people management. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. Learning and certification support is available for tools and frameworks directly relevant to the role. 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. The package is structured with a fixed component, performance bonus, and standard health coverage. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. High performers in this role typically move into a broader ownership scope within 18-24 months. Most days include at least one review checkpoint where progress is discussed against the plan for the week. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work.
**Department:** AI for Cybersecurity | **Industry:** Machine Learning
**Location:** Hybrid - Pune | **Job Type:** Full-time | **CTC:** INR 53.8-79.2 LPA
### Role Overview
This position calls for an AI Security Technology Strategist who can take ownership of core responsibilities within our AI for Cybersecurity team. The role is positioned at the senior level and reports into the broader AI for Cybersecurity charter.
### Key Responsibilities
- Own end-to-end delivery of tasks related to ai for cybersecurity.
- Apply working knowledge of Statistical Modelling and Data Preprocessing to daily execution.
- Coordinate with cross-functional stakeholders within Machine Learning.
- Maintain documentation and reporting as required by the team lead.
- Flag risks and blockers early rather than at review checkpoints.
### Requirements
- M.Tech (Machine Learning) or equivalent qualification.
- 10 years of relevant experience (senior level).
- Working proficiency in: Statistical Modelling, Data Preprocessing, Machine Learning Algorithms, AI for Cybersecurity, Python, Deep Learning, Cloud Platforms (AWS/GCP).
### Additional Notes
Interested candidates should be prepared to walk through relevant past work during the interview process. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Compensation includes standard statutory benefits along with performance-linked variable pay. The role alternates between independent deep work and short coordination huddles with stakeholders across functions. Relocation assistance may be extended for candidates moving from a different city, subject to approval. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. 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. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. There is a defined internal mobility path for people who want to specialise deeper or move into people management. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. Learning and certification support is available for tools and frameworks directly relevant to the role. 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. The package is structured with a fixed component, performance bonus, and standard health coverage. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. High performers in this role typically move into a broader ownership scope within 18-24 months. Most days include at least one review checkpoint where progress is discussed against the plan for the week. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work.