Job Description
AIOps Center of Excellence Lead | Coimbatore | INR 12.0-74.7 LPA
AI Operations (AIOps) role, senior level, full-time.
Need: Ph.D (AI), 15+ yrs.
Core skills: TensorFlow/PyTorch, Python, Deep Learning, Cloud Platforms (AWS/GCP/Azure), Statistical Modelling.
If this fits your profile in ai operations (aiops), apply now.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
The next logical step from this position is a senior or lead-track role within the same function. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
High performers in this role typically move into a broader ownership scope within 18-24 months. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. 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.
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.
Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Internal job postings are open to employees who've completed a minimum tenure in their current role. Interested candidates should be prepared to walk through relevant past work during the interview process.
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.
No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. Compensation includes standard statutory benefits along with performance-linked variable pay.
Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. Learning and certification support is available for tools and frameworks directly relevant to the role.
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.
Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. References may be requested closer to the offer stage rather than at the start of the process. 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. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
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.
Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.
AI Operations (AIOps) role, senior level, full-time.
Need: Ph.D (AI), 15+ yrs.
Core skills: TensorFlow/PyTorch, Python, Deep Learning, Cloud Platforms (AWS/GCP/Azure), Statistical Modelling.
If this fits your profile in ai operations (aiops), apply now.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
The next logical step from this position is a senior or lead-track role within the same function. Most days include at least one review checkpoint where progress is discussed against the plan for the week.
High performers in this role typically move into a broader ownership scope within 18-24 months. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. 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.
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.
Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Internal job postings are open to employees who've completed a minimum tenure in their current role. Interested candidates should be prepared to walk through relevant past work during the interview process.
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.
No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. Compensation includes standard statutory benefits along with performance-linked variable pay.
Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. Learning and certification support is available for tools and frameworks directly relevant to the role.
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.
Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. References may be requested closer to the offer stage rather than at the start of the process. 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. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
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.
Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.