Job Description
Looking for a Global AI Operations Manager who's genuinely interested in AI Operations (AIOps) and wants to make an impact from day one.
You'll be working out of Gurugram (full-time), and honestly, the day-to-day is going to revolve around AI Operations (AIOps) and TensorFlow/PyTorch. We're not looking for someone who just ticks boxes - we want someone who actually cares about ai operations (aiops).
On paper, we'd expect Ph.D (AI) and somewhere around 15 years of experience, but we're just as interested in how you think as in what's on your resume.
Pay-wise, we're offering INR 37.5-64.6 LPA - fair for the senior level band and open to discussion based on what you bring.
There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
High performers in this role typically move into a broader ownership scope within 18-24 months. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.
The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. 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.
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.
Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. References may be requested closer to the offer stage rather than at the start of the process. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. Relocation assistance may be extended for candidates moving from a different city, subject to approval.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. Internal job postings are open to employees who've completed a minimum tenure in their current role.
You'll be working out of Gurugram (full-time), and honestly, the day-to-day is going to revolve around AI Operations (AIOps) and TensorFlow/PyTorch. We're not looking for someone who just ticks boxes - we want someone who actually cares about ai operations (aiops).
On paper, we'd expect Ph.D (AI) and somewhere around 15 years of experience, but we're just as interested in how you think as in what's on your resume.
Pay-wise, we're offering INR 37.5-64.6 LPA - fair for the senior level band and open to discussion based on what you bring.
There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
High performers in this role typically move into a broader ownership scope within 18-24 months. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.
The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. 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.
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.
Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. References may be requested closer to the offer stage rather than at the start of the process. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. Relocation assistance may be extended for candidates moving from a different city, subject to approval.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. Internal job postings are open to employees who've completed a minimum tenure in their current role.