Job Description
Junior Intelligent Agent Engineer | Chennai | INR 2.9-18.3 LPA
Conversational AI role, junior level, internship.
Need: B.Tech (CS/AI), 0+ yrs.
Core skills: Conversational AI, Natural Language Processing, Model Deployment (MLOps), Python.
If this fits your profile in conversational ai, apply now.
The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
Compensation includes standard statutory benefits along with performance-linked variable pay. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. 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. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy.
Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. The organisation has historically promoted from within for a majority of its senior and lead openings. The next logical step from this position is a senior or lead-track role within the same function.
Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. High performers in this role typically move into a broader ownership scope within 18-24 months.
Conversational AI role, junior level, internship.
Need: B.Tech (CS/AI), 0+ yrs.
Core skills: Conversational AI, Natural Language Processing, Model Deployment (MLOps), Python.
If this fits your profile in conversational ai, apply now.
The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables.
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
Compensation includes standard statutory benefits along with performance-linked variable pay. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. 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. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy.
Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. The organisation has historically promoted from within for a majority of its senior and lead openings. The next logical step from this position is a senior or lead-track role within the same function.
Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. High performers in this role typically move into a broader ownership scope within 18-24 months.