Job Description
**AI Operations Engineer – DevOps** | Coimbatore | Hybrid | INR 9.5-28.3 LPA
**About the role:**
- Position within AI Operations (AIOps), under the Artificial Intelligence (AI) vertical
- Level: mid level
- Reports to the functional head for AI Operations (AIOps)
**What you'll do:**
- Handle core ai operations (aiops) activities on a day-to-day basis
- Use Model Deployment (MLOps) 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:**
- Model Deployment (MLOps)
- Computer Vision
- Natural Language Processing
- Python
- AI Operations (AIOps)
- Machine Learning
- Data Preprocessing
- M.Sc (Data Science)
- 7+ years of relevant experience
**Good to know:**
- There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Interested candidates should be prepared to walk through relevant past work during the interview process.
- Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
- 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. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
- 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. 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. High performers in this role typically move into a broader ownership scope within 18-24 months.
- New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here.
- Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. The organisation has historically promoted from within for a majority of its senior and lead openings.
- Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. 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. There is a defined internal mobility path for people who want to specialise deeper or move into people management.
- The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.
**About the role:**
- Position within AI Operations (AIOps), under the Artificial Intelligence (AI) vertical
- Level: mid level
- Reports to the functional head for AI Operations (AIOps)
**What you'll do:**
- Handle core ai operations (aiops) activities on a day-to-day basis
- Use Model Deployment (MLOps) 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:**
- Model Deployment (MLOps)
- Computer Vision
- Natural Language Processing
- Python
- AI Operations (AIOps)
- Machine Learning
- Data Preprocessing
- M.Sc (Data Science)
- 7+ years of relevant experience
**Good to know:**
- There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Interested candidates should be prepared to walk through relevant past work during the interview process.
- Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round.
- 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. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
- 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. 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. High performers in this role typically move into a broader ownership scope within 18-24 months.
- New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here.
- Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. The organisation has historically promoted from within for a majority of its senior and lead openings.
- Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. 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. There is a defined internal mobility path for people who want to specialise deeper or move into people management.
- The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.