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Role overview
Job description
About ZenteiQ ZenteiQ is building AI-powered products and software infrastructure for intelligent applications and scientific workflows. About the Role We are looking for an AI/ML Engineer to build and scale the AI capabilities powering our products. The role will focus on LLM applications, AI agents, RAG, memory, tool calling, evaluation and supporting backend services required to run these systems reliably in production. What You'll Do - Build production applications using LLMs and AI agents. - Design multi-step workflows with tool/function calling. - Build and improve RAG, retrieval and context management pipelines. - Implement conversation state and memory for AI applications. - Build structured and streaming LLM workflows. - Develop backend APIs and services supporting AI features. - Evaluate, debug and improve AI system quality and reliability. - Work with product, backend and infrastructure teams to ship AI capabilities to production. What We're Looking For - 2-6 years of AI/ML engineering experience. - Strong programming skills in Python; experience with other programming languages is a plus. - Hands-on experience building applications using LLMs. - Experience with AI agents or multi-step LLM workflows. - Good understanding of RAG, embeddings, vector search and retrieval. - Experience with tool/function calling and structured outputs. - Experience building backend APIs using FastAPI or similar frameworks. - Good understanding of asynchronous programming and databases. - Strong debugging and problem-solving skills. - Ability to take AI features from prototype to production. Good to Have / Bonus Points - LangGraph, LangChain or similar frameworks. - Vector databases and reranking. - LLM evaluation and observability. - Knowledge graphs or graph-based retrieval. - Redis or messaging/queue systems. - Docker, Kubernetes and cloud platforms. What We'll Evaluate - Python and software engineering fundamentals. - LLM and agentic workflow design. - RAG and retrieval fundamentals. - Tool calling, memory and state management. - Backend API and async programming fundamentals. - Debugging, reliability and production engineering. Why ZenteiQ - Build AI systems used in real products. - Work on LLMs, agents, retrieval and intelligent workflows. - Solve practical production problems around reliability, context and scalability. - Own AI features from development to production.
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About this listing
- Source: ZenteiQ's official careers site · still listed there on 9 Nov 2026
- Posted 4 Sept 2026
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Role market pulse
How Machine Learning Engineer demand looks in India
Live jobs
43
Posted 30d
25
30d movement
+108.3%
Remote share
16.3%
Salary listed
11.6%
Salary trend 1Y
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What they are looking for
Skills & requirements
Qualification
The role will focus on LLM applications, AI agents, RAG, memory, tool calling, evaluation and supporting backend services required to run these systems reliably in production; Build structured and streaming LLM workflows; Experience with AI agents or multi-step LLM workflows; LLM evaluation and observability
Department · AI Product Engineering
Hiring company
ZenteiQ
ZenteiQ builds foundation models from scratch in India and the products that put them to work in industry, deployed on enterprise infrastructure including fully offline environments.
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₹28.2L – ₹34.9L/yr
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