Job Description
Here's the deal: we need an AI Product Strategy Director who can hit the ground running on AI Strategy & Consulting work.
You'll be working out of Remote (Pan India) (full-time), and honestly, the day-to-day is going to revolve around TensorFlow/PyTorch and Deep Learning. We're not looking for someone who just ticks boxes - we want someone who actually cares about ai strategy & consulting.
On paper, we'd expect M.Sc (Data Science) and somewhere around 8 years of experience, but we're just as interested in how you think as in what's on your resume.
Pay-wise, we're offering INR 31.4-59.5 LPA - fair for the senior level band and open to discussion based on what you bring.
Interested candidates should be prepared to walk through relevant past work during the interview process. The organisation has historically promoted from within for a majority of its senior and lead openings. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
Most days include at least one review checkpoint where progress is discussed against the plan for the week. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
The role alternates between independent deep work and short coordination huddles with stakeholders across functions. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability.
The package is structured with a fixed component, performance bonus, and standard health coverage. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. Learning and certification support is available for tools and frameworks directly relevant to the role.
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.
Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
High performers in this role typically move into a broader ownership scope within 18-24 months. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.
You'll be working out of Remote (Pan India) (full-time), and honestly, the day-to-day is going to revolve around TensorFlow/PyTorch and Deep Learning. We're not looking for someone who just ticks boxes - we want someone who actually cares about ai strategy & consulting.
On paper, we'd expect M.Sc (Data Science) and somewhere around 8 years of experience, but we're just as interested in how you think as in what's on your resume.
Pay-wise, we're offering INR 31.4-59.5 LPA - fair for the senior level band and open to discussion based on what you bring.
Interested candidates should be prepared to walk through relevant past work during the interview process. The organisation has historically promoted from within for a majority of its senior and lead openings. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
Most days include at least one review checkpoint where progress is discussed against the plan for the week. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
The role alternates between independent deep work and short coordination huddles with stakeholders across functions. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability.
The package is structured with a fixed component, performance bonus, and standard health coverage. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. Learning and certification support is available for tools and frameworks directly relevant to the role.
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.
Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
High performers in this role typically move into a broader ownership scope within 18-24 months. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership.