Job Description
The organisation is seeking a qualified Virtual Assistant Developer – Mid-level to support ongoing initiatives in AI Chatbots. This is a mid level opening based out of Mumbai, offered on a full-time (wfh) basis.
The ideal candidate holds B.Tech (CS/AI) and brings roughly 5 years of hands-on exposure to ai chatbots. Day-to-day, the work draws heavily on AI Chatbots, Model Deployment (MLOps), Deep Learning, Data Preprocessing, and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 5.2-21.5 LPA, in line with market standards for mid level roles within artificial intelligence (ai).
The role alternates between independent deep work and short coordination huddles with stakeholders across functions. Internal job postings are open to employees who've completed a minimum tenure in their current role.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy.
Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done.
The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
Interested candidates should be prepared to walk through relevant past work during the interview process. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work.
The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. The package is structured with a fixed component, performance bonus, and standard health coverage.
Learning and certification support is available for tools and frameworks directly relevant to the role. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments.
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. The next logical step from this position is a senior or lead-track role within the same function.
There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. High performers in this role typically move into a broader ownership scope within 18-24 months.
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here.
Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
This role offers a genuine opportunity to build depth in AI Chatbots while working alongside an experienced team.
The ideal candidate holds B.Tech (CS/AI) and brings roughly 5 years of hands-on exposure to ai chatbots. Day-to-day, the work draws heavily on AI Chatbots, Model Deployment (MLOps), Deep Learning, Data Preprocessing, and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 5.2-21.5 LPA, in line with market standards for mid level roles within artificial intelligence (ai).
The role alternates between independent deep work and short coordination huddles with stakeholders across functions. Internal job postings are open to employees who've completed a minimum tenure in their current role.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy.
Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done.
The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
Interested candidates should be prepared to walk through relevant past work during the interview process. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work.
The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. The package is structured with a fixed component, performance bonus, and standard health coverage.
Learning and certification support is available for tools and frameworks directly relevant to the role. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments.
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. The next logical step from this position is a senior or lead-track role within the same function.
There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. High performers in this role typically move into a broader ownership scope within 18-24 months.
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here.
Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
This role offers a genuine opportunity to build depth in AI Chatbots while working alongside an experienced team.