Job Description
## AI Ethical AI Program Lead
**Department:** AI Governance & Compliance | **Industry:** Artificial Intelligence (AI)
**Location:** Hybrid - Bengaluru | **Job Type:** Full-time | **CTC:** INR 13.5-36.5 LPA
### Role Overview
This position calls for an AI Ethical AI Program Lead who can take ownership of core responsibilities within our AI Governance & Compliance team. The role is positioned at the mid level and reports into the broader AI Governance & Compliance charter.
### Key Responsibilities
- Own end-to-end delivery of tasks related to ai governance & compliance.
- Apply working knowledge of Model Deployment (MLOps) and Cloud Platforms (AWS/GCP/Azure) to daily execution.
- Coordinate with cross-functional stakeholders within Artificial Intelligence (AI).
- Maintain documentation and reporting as required by the team lead.
- Flag risks and blockers early rather than at review checkpoints.
### Requirements
- M.Tech (AI/ML) or equivalent qualification.
- 7 years of relevant experience (mid level).
- Working proficiency in: Model Deployment (MLOps), Cloud Platforms (AWS/GCP/Azure), Compliance, Statistical Modelling, AI Governance, Neural Network Architectures, Deep Learning.
### Additional Notes
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. High performers in this role typically move into a broader ownership scope within 18-24 months. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. Internal job postings are open to employees who've completed a minimum tenure in their current role. 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. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. Interested candidates should be prepared to walk through relevant past work during the interview process. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. 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. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. 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.
**Department:** AI Governance & Compliance | **Industry:** Artificial Intelligence (AI)
**Location:** Hybrid - Bengaluru | **Job Type:** Full-time | **CTC:** INR 13.5-36.5 LPA
### Role Overview
This position calls for an AI Ethical AI Program Lead who can take ownership of core responsibilities within our AI Governance & Compliance team. The role is positioned at the mid level and reports into the broader AI Governance & Compliance charter.
### Key Responsibilities
- Own end-to-end delivery of tasks related to ai governance & compliance.
- Apply working knowledge of Model Deployment (MLOps) and Cloud Platforms (AWS/GCP/Azure) to daily execution.
- Coordinate with cross-functional stakeholders within Artificial Intelligence (AI).
- Maintain documentation and reporting as required by the team lead.
- Flag risks and blockers early rather than at review checkpoints.
### Requirements
- M.Tech (AI/ML) or equivalent qualification.
- 7 years of relevant experience (mid level).
- Working proficiency in: Model Deployment (MLOps), Cloud Platforms (AWS/GCP/Azure), Compliance, Statistical Modelling, AI Governance, Neural Network Architectures, Deep Learning.
### Additional Notes
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. High performers in this role typically move into a broader ownership scope within 18-24 months. Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. Internal job postings are open to employees who've completed a minimum tenure in their current role. 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. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. Interested candidates should be prepared to walk through relevant past work during the interview process. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. 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. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. 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.