Job Description
**AI Security Infrastructure Architect** | Ahmedabad | Full-time | INR 37.8-73.4 LPA
**About the role:**
- Position within AI for Cybersecurity, under the Machine Learning vertical
- Level: senior level
- Reports to the functional head for AI for Cybersecurity
**What you'll do:**
- Handle core ai for cybersecurity activities on a day-to-day basis
- Use Computer Vision/NLP Basics 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:**
- Computer Vision/NLP Basics
- Model Evaluation & Tuning
- AI for Cybersecurity
- MLOps
- Feature Engineering
- TensorFlow/PyTorch
- Deep Learning
- Python
- Machine Learning Algorithms
- M.Sc (Data Science)
- 9+ years of relevant experience
**Good to know:**
- High performers in this role typically move into a broader ownership scope within 18-24 months. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.
- The package is structured with a fixed component, performance bonus, and standard health coverage. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
- The next logical step from this position is a senior or lead-track role within the same function. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
- Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
- Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
- Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Learning and certification support is available for tools and frameworks directly relevant to the role. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments.
- Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions.
- No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
**About the role:**
- Position within AI for Cybersecurity, under the Machine Learning vertical
- Level: senior level
- Reports to the functional head for AI for Cybersecurity
**What you'll do:**
- Handle core ai for cybersecurity activities on a day-to-day basis
- Use Computer Vision/NLP Basics 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:**
- Computer Vision/NLP Basics
- Model Evaluation & Tuning
- AI for Cybersecurity
- MLOps
- Feature Engineering
- TensorFlow/PyTorch
- Deep Learning
- Python
- Machine Learning Algorithms
- M.Sc (Data Science)
- 9+ years of relevant experience
**Good to know:**
- High performers in this role typically move into a broader ownership scope within 18-24 months. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.
- The package is structured with a fixed component, performance bonus, and standard health coverage. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
- The next logical step from this position is a senior or lead-track role within the same function. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
- Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
- Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
- Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Learning and certification support is available for tools and frameworks directly relevant to the role. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments.
- Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions.
- No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Most days include at least one review checkpoint where progress is discussed against the plan for the week.