Senior Generative Ai EngineerYarnit • Bengaluru, Republic Of India, IN

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Senior Generative Ai Engineer

Yarnit • Bengaluru, Republic Of India, IN

2 days ago

Job description

Senior AI Engineer (Generative AI)

Location : Bangalore, India (Hybrid)

Experience : 3–5 years

About Yarnit

Yarnit is building the future of Agentic AI — where autonomous, context-aware AI systems transform how enterprises strategize, create, and operate. Our multi-agent orchestration framework powers enterprise-grade copilots and autonomous workflows across marketing, commerce, and industrial domains.

Job Description

You will lead the development of multi-agent AI systems and advanced generative AI solutions across Yarnit’s platform and client deployments.

Key Responsibilities

Design and develop production-grade multi-agent systems (planning, tools, memory, evaluation).

Implement LLM architectures and fine-tuning (e.G., PEFT / LoRA) with alignment / safety practices.

Architect advanced RAG end-to-end (using vector , SQL , or knowledge graph approaches).

Build agent orchestration frameworks and prompt engineering tooling with tracing / observability.

Develop semantic search and retrieval pipelines;

maintain data freshnessand evaluation loops.

Collaborate with product and client teams to deliver solutions from design to deployment.

Build and maintain cloud AI infrastructure with MLOps (CI / CD, registries, monitoring).

Required Skills & Qualifications (Must-have)

3–5 years of professional experience building Generative AI applications with LLMs.

Hands-on, production experience with multi-agent frameworks (e.G., Autogen, LangGraph, CrewAI, LangChain Agents).

Expert Python and solid software architecture / testing practices.

Strong data science foundation with pandas for analysis, feature prep, and evaluation.

Proven delivery of advanced RAG (vector retrieval, SQL agents for grounded queries, and KG-based retrieval where appropriate).

Experience with model fine-tuning and alignment techniques.

Cloud experience (AWS / GCP / Azure), containerization (Docker), and orchestration (Kubernetes / Batch).

Working knowledge of MLOps (model registries, CI / CD, offline / online evaluations, monitoring).

Preferred Qualifications

Experience with multimodal models (text / image / audio) and tool-using VLMs.

Practical exposure to knowledge graphs (basic modeling / querying) in retrieval workflows.

Prior work on content / marketing AI or enterprise copilots.

Open-source contributions or relevant publications.

Understanding of Responsible AI (evaluation, safety, governance).

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Generative Ai Engineer • Bengaluru, Republic Of India, IN

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