Job Description
We are looking to onboard an AI Marketing Program Manager to strengthen our AI-driven Marketing function within Artificial Intelligence (AI). This is a senior level opening based out of Kochi, offered on a hybrid basis.
The ideal candidate holds Ph.D (AI) and brings roughly 14 years of hands-on exposure to ai-driven marketing. Day-to-day, the work draws heavily on Computer Vision, Neural Network Architectures, Machine Learning, Cloud Platforms (AWS/GCP/Azure), and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 52.5-106.7 LPA, in line with market standards for senior level roles within artificial intelligence (ai).
Internal job postings are open to employees who've completed a minimum tenure in their current role. Relocation assistance may be extended for candidates moving from a different city, subject to approval.
The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
Learning and certification support is available for tools and frameworks directly relevant to the role. The package is structured with a fixed component, performance bonus, and standard health coverage.
Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. Compensation includes standard statutory benefits along with performance-linked variable pay.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. 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. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work.
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.
The role alternates between independent deep work and short coordination huddles with stakeholders across functions. Interested candidates should be prepared to walk through relevant past work during the interview process.
References may be requested closer to the offer stage rather than at the start of the process. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. 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. 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.
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability.
The organisation has historically promoted from within for a majority of its senior and lead openings. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
This is a good fit for someone who wants real ownership rather than a purely execution-only role.
The ideal candidate holds Ph.D (AI) and brings roughly 14 years of hands-on exposure to ai-driven marketing. Day-to-day, the work draws heavily on Computer Vision, Neural Network Architectures, Machine Learning, Cloud Platforms (AWS/GCP/Azure), and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 52.5-106.7 LPA, in line with market standards for senior level roles within artificial intelligence (ai).
Internal job postings are open to employees who've completed a minimum tenure in their current role. Relocation assistance may be extended for candidates moving from a different city, subject to approval.
The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
Learning and certification support is available for tools and frameworks directly relevant to the role. The package is structured with a fixed component, performance bonus, and standard health coverage.
Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. Compensation includes standard statutory benefits along with performance-linked variable pay.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. 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. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work.
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.
The role alternates between independent deep work and short coordination huddles with stakeholders across functions. Interested candidates should be prepared to walk through relevant past work during the interview process.
References may be requested closer to the offer stage rather than at the start of the process. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. 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. 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.
Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability.
The organisation has historically promoted from within for a majority of its senior and lead openings. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
This is a good fit for someone who wants real ownership rather than a purely execution-only role.