Job Description
## AI Ethics & Compliance Trainee
**Department:** AI Governance & Compliance | **Industry:** Artificial Intelligence (AI)
**Location:** Bhubaneswar | **Job Type:** Full-time (WFH) | **CTC:** INR 13.4-29.1 LPA
### Role Overview
The organisation is seeking a qualified AI Ethics & Compliance Trainee to support ongoing initiatives in AI Governance & Compliance. The role is positioned at the junior 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 Compliance and AI Governance 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.
- 1 years of relevant experience (junior level).
- Working proficiency in: Compliance, AI Governance, Cloud Platforms (AWS/GCP/Azure), Computer Vision, Neural Network Architectures.
### Additional Notes
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. The organisation has historically promoted from within for a majority of its senior and lead openings. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Compensation includes standard statutory benefits along with performance-linked variable pay. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. References may be requested closer to the offer stage rather than at the start of the process. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. The role alternates between independent deep work and short coordination huddles with stakeholders across functions. Most days include at least one review checkpoint where progress is discussed against the plan for the week. Learning and certification support is available for tools and frameworks directly relevant to the role. 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.
**Department:** AI Governance & Compliance | **Industry:** Artificial Intelligence (AI)
**Location:** Bhubaneswar | **Job Type:** Full-time (WFH) | **CTC:** INR 13.4-29.1 LPA
### Role Overview
The organisation is seeking a qualified AI Ethics & Compliance Trainee to support ongoing initiatives in AI Governance & Compliance. The role is positioned at the junior 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 Compliance and AI Governance 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.
- 1 years of relevant experience (junior level).
- Working proficiency in: Compliance, AI Governance, Cloud Platforms (AWS/GCP/Azure), Computer Vision, Neural Network Architectures.
### Additional Notes
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. The organisation has historically promoted from within for a majority of its senior and lead openings. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Compensation includes standard statutory benefits along with performance-linked variable pay. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. References may be requested closer to the offer stage rather than at the start of the process. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. The role alternates between independent deep work and short coordination huddles with stakeholders across functions. Most days include at least one review checkpoint where progress is discussed against the plan for the week. Learning and certification support is available for tools and frameworks directly relevant to the role. 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.