Job Description
This position calls for an AI & BI Systems Engineer who can take ownership of core responsibilities within our AI for Business Intelligence team. This is a mid level opening based out of Hybrid - Bengaluru, offered on a hybrid basis.
The ideal candidate holds M.Tech (AI/ML) and brings roughly 6 years of hands-on exposure to ai for business intelligence. Day-to-day, the work draws heavily on Python, Data Preprocessing, Deep Learning, Machine Learning, and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 5.4-36.6 LPA, in line with market standards for mid level roles within artificial intelligence (ai).
Learning and certification support is available for tools and frameworks directly relevant to the role. Interested candidates should be prepared to walk through relevant past work during the interview process.
Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments.
Compensation includes standard statutory benefits along with performance-linked variable pay. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
References may be requested closer to the offer stage rather than at the start of the process. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
Relocation assistance may be extended for candidates moving from a different city, subject to approval. The package is structured with a fixed component, performance bonus, and standard health coverage.
New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
High performers in this role typically move into a broader ownership scope within 18-24 months. The role alternates between independent deep work and short coordination huddles with stakeholders across functions. The next logical step from this position is a senior or lead-track role within the same function.
The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done.
This is a good fit for someone who wants real ownership rather than a purely execution-only role.
The ideal candidate holds M.Tech (AI/ML) and brings roughly 6 years of hands-on exposure to ai for business intelligence. Day-to-day, the work draws heavily on Python, Data Preprocessing, Deep Learning, Machine Learning, and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 5.4-36.6 LPA, in line with market standards for mid level roles within artificial intelligence (ai).
Learning and certification support is available for tools and frameworks directly relevant to the role. Interested candidates should be prepared to walk through relevant past work during the interview process.
Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments.
Compensation includes standard statutory benefits along with performance-linked variable pay. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
References may be requested closer to the offer stage rather than at the start of the process. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
Relocation assistance may be extended for candidates moving from a different city, subject to approval. The package is structured with a fixed component, performance bonus, and standard health coverage.
New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
High performers in this role typically move into a broader ownership scope within 18-24 months. The role alternates between independent deep work and short coordination huddles with stakeholders across functions. The next logical step from this position is a senior or lead-track role within the same function.
The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done.
This is a good fit for someone who wants real ownership rather than a purely execution-only role.