ApplySarthi

Senior Gen AI Engineer

MantriAI

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102 open gen roles across 40 companies are on ApplySarthi right now, most of them in Bengaluru (11), Delhi NCR (5), Hyderabad (3).

What gen roles keep asking for: Python (30%), Generative AI (29%), AWS (23%), LLMs (23%), RAG (22%), Machine learning (17%), Docker (16%), Azure (15%) — counted across their open postings here.

Generative AI jobs · LLMs jobs · Machine learning jobs

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Interviews for gen roles keep coming back to Python, Generative AI, AWS, LLMs. Practise those questions before you sit with MantriAI.

Questions you are likely to be asked

  1. Why do you want to join MantriAI?
  2. What is your experience with Generative AI? Tell me one thing you learned the hard way.
  3. Tell me about a time the data was messy or wrong. What did you do?
  4. How would you explain your model's result to someone who is not technical?
  5. What would you check first if a model's accuracy dropped after going live?

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Position : Senior Gen AI Engineer EXxperience : 6+ Years About MantriAI MantriAI is the search partner for the company on this role. Every application comes to us first. We screen, and only shortlisted profiles go to the company. This post is for a well funded early stage company building an AI platform for industrial reliability, working with oil and gas, chemicals, manufacturing, utilities and automotive. The product watches critical plant equipment, predicts what is going to fail, explains why, and tells a reliability engineer what to do next. Founded in 2024, headquartered in the United States with engineering built out of India, and funded with about ₹58 Cr raised in early 2026. Enterprise deployments are already live. What you will do Build agentic workflows for diagnostics and root cause analysis. Agents that plan, call tools including the numerical models and the plant historian, and produce a recommendation an engineer will act on. Lead engineering initiatives aimed at the continuous enhancement of the AI platform, with a focus on the rapid development and iteration of scalable, robust distributed infrastructure to support machine learning training, inference, and evaluation. Build and own the asset knowledge graph: equipment hierarchy, failure modes, ontology and schema design, entity resolution across messy plant records, and retrieval that reasons over the graph. Build multimodal extraction over P&IDs, OEM manuals, inspection reports, maintenance work orders and plant imagery, with accuracy measured per field. Take all of it into customer environments. VPC, on-premise and at the edge, because plants are often air-gapped or short on bandwidth. Define and articulate the long-term strategic vision for company's GenAI platform, and mentor engineers as the team grows. What we are looking for 6+ years in engineering, with at least eighteen months of it building LLM systems that shipped and stayed in production. Depth in at least one of: agent systems, knowledge graphs and graph retrieval, document and multimodal extraction. Hands-on agent work is required, since the product is an agent platform. A track record of taking systems to scale, on high data volume and awkward data structures. You can explain how you knew a system was working, and what the worst thing was that it did in production. Comfortable working alongside domain experts, and comfortable being the first person on something. Good to have Classical machine learning or statistical modelling in your background. Exposure to industry: plants, asset management, reliability, maintenance, IIoT. Real-time systems, or edge and on-premise LLM deployment. An advanced degree in computer science, data science, applied mathematics or engineering. Not this role Model training and fine-tuning as the main craft. Inference infrastructure and GPU serving on its own. A peoplemanagement seat. This one is hands-on first. Details Compensation: ₹65-85 LPA plus ESOP Location: Remote today. Open to moving to Bangalore once office opens end of 2026 Notice: We are prioritizing 30 to 45 days Location and other Remote for now. The Bengaluru office is expected to open in the next six to ten months and this role moves there, so relocating to Bengaluru needs to work for you. The founders are based in the United States, so expect some Pacific time overlap in the week. Process A short call with MantriAI, then three rounds with Spector: the co-founder and CTO, a technical round, and a final conversation with the CEO. Posted by MantriAI, search partner for the company. Shortlisted applications hear from us within 48 hours.

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Listed on wellfound · posted 2026-08-28. ApplySarthi collects openings and links to application pages; the role is advertised by MantriAI, not by us.