Job Description
This position calls for an AI Monitoring & Insights Engineer who can take ownership of core responsibilities within our AI Operations (AIOps) team. This is a mid level opening based out of Bhubaneswar, offered on a full-time basis.
The ideal candidate holds M.Tech (AI/ML) and brings roughly 6 years of hands-on exposure to ai operations (aiops). Day-to-day, the work draws heavily on Natural Language Processing, TensorFlow/PyTorch, Deep Learning, AI Operations (AIOps), and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 6.8-32.6 LPA, in line with market standards for mid level roles within artificial intelligence (ai).
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. 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. 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. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done.
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.
Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
The package is structured with a fixed component, performance bonus, and standard health coverage. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. There is a defined internal mobility path for people who want to specialise deeper or move into people management.
Most days include at least one review checkpoint where progress is discussed against the plan for the week. Learning and certification support is available for tools and frameworks directly relevant to the role.
High performers in this role typically move into a broader ownership scope within 18-24 months. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
The role alternates between independent deep work and short coordination huddles with stakeholders across functions. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Relocation assistance may be extended for candidates moving from a different city, subject to approval.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. 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. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
If your background aligns with the above and you're looking for your next step in AI Operations (AIOps), we'd like to hear from you.
The ideal candidate holds M.Tech (AI/ML) and brings roughly 6 years of hands-on exposure to ai operations (aiops). Day-to-day, the work draws heavily on Natural Language Processing, TensorFlow/PyTorch, Deep Learning, AI Operations (AIOps), and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 6.8-32.6 LPA, in line with market standards for mid level roles within artificial intelligence (ai).
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. 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. 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. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done.
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.
Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
The package is structured with a fixed component, performance bonus, and standard health coverage. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. There is a defined internal mobility path for people who want to specialise deeper or move into people management.
Most days include at least one review checkpoint where progress is discussed against the plan for the week. Learning and certification support is available for tools and frameworks directly relevant to the role.
High performers in this role typically move into a broader ownership scope within 18-24 months. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
The role alternates between independent deep work and short coordination huddles with stakeholders across functions. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Relocation assistance may be extended for candidates moving from a different city, subject to approval.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. 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. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
If your background aligns with the above and you're looking for your next step in AI Operations (AIOps), we'd like to hear from you.