Job Description
## Generative AI Program Manager
**Department:** Generative AI | **Industry:** Machine Learning
**Location:** Kochi | **Job Type:** Full-time | **CTC:** INR 38.3-94.3 LPA
### Role Overview
We are looking to onboard a Generative AI Program Manager to strengthen our Generative AI function within Machine Learning. The role is positioned at the senior level and reports into the broader Generative AI charter.
### Key Responsibilities
- Own end-to-end delivery of tasks related to generative ai.
- Apply working knowledge of MLOps and Statistical Modelling to daily execution.
- Coordinate with cross-functional stakeholders within Machine Learning.
- Maintain documentation and reporting as required by the team lead.
- Flag risks and blockers early rather than at review checkpoints.
### Requirements
- M.Tech (Machine Learning) or equivalent qualification.
- 14 years of relevant experience (senior level).
- Working proficiency in: MLOps, Statistical Modelling, Cloud Platforms (AWS/GCP), Generative AI, Data Preprocessing, Machine Learning Algorithms, Python.
### Additional Notes
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. 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. 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. There is a defined internal mobility path for people who want to specialise deeper or move into people management. 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. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. Relocation assistance may be extended for candidates moving from a different city, subject to approval. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. References may be requested closer to the offer stage rather than at the start of the process. Internal job postings are open to employees who've completed a minimum tenure in their current role. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. 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. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
**Department:** Generative AI | **Industry:** Machine Learning
**Location:** Kochi | **Job Type:** Full-time | **CTC:** INR 38.3-94.3 LPA
### Role Overview
We are looking to onboard a Generative AI Program Manager to strengthen our Generative AI function within Machine Learning. The role is positioned at the senior level and reports into the broader Generative AI charter.
### Key Responsibilities
- Own end-to-end delivery of tasks related to generative ai.
- Apply working knowledge of MLOps and Statistical Modelling to daily execution.
- Coordinate with cross-functional stakeholders within Machine Learning.
- Maintain documentation and reporting as required by the team lead.
- Flag risks and blockers early rather than at review checkpoints.
### Requirements
- M.Tech (Machine Learning) or equivalent qualification.
- 14 years of relevant experience (senior level).
- Working proficiency in: MLOps, Statistical Modelling, Cloud Platforms (AWS/GCP), Generative AI, Data Preprocessing, Machine Learning Algorithms, Python.
### Additional Notes
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. 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. 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. There is a defined internal mobility path for people who want to specialise deeper or move into people management. 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. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. Relocation assistance may be extended for candidates moving from a different city, subject to approval. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. References may be requested closer to the offer stage rather than at the start of the process. Internal job postings are open to employees who've completed a minimum tenure in their current role. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. 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. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.