Senior GenAI Engineer (Python + React + Agentic AI)

Zemoso Technologies; Bengaluru; On-site; INR 1,400,000 - 2,100,000; Full time

Job summary

Zemoso Technologies in Bengaluru is seeking a Senior GenAI Engineer with strong engineering foundations to own GenAI features end-to-end, spanning backend (Python/Django/FastAPI) and frontend (React). You will work on agentic AI workflows, design RAG pipelines, and mentor junior engineers while handling ambiguous requirements.

Ideal candidates have 5–8 years of overall experience, 3–4+ years in GenAI production, and hands-on delivery of GenAI solutions across backend and frontend with cloud

Qualifications

• Hands-on experience building GenAI applications in production.
• Experience with RAG pipelines, Embeddings, and Retrieval strategies.
• Design and implement GenAI features across backend and frontend.

Responsibilities

• Build and deploy GenAI-powered features across backend and frontend.
• Design RAG architectures and retrieval strategies.
• Own GenAI solutions end-to-end from design to production rollout.
• Develop agent-based workflows and multi-step reasoning.
• Mentor junior engineers and review GenAI code.

Skills

Python/Django

React/Svelte

GenAI in production

RAG pipelines

Vector databases

LLM APIs

Agentic AI

API design

Cloud: GCP/Azure

Tools

Vector databases

Job description

Location

Bangalore, or candidates ready to relocate to Bangalore.

Role Overview

We are looking for a Senior GenAI Engineer with strong core engineering foundations and hands-on experience building and deploying GenAI solutions. This role is execution- and ownership-focused - responsible for delivering GenAI features end-to-end (backend + frontend), working with agentic AI workflows, and mentoring junior engineers while handling ambiguous requirements. This position is part of our GenAI hiring phase, where we prioritize strong full-stack/backend engineers who have recently built and shipped GenAI and agentic AI solutions in production.

Experience Profile

• Overall experience: 5-8 years


• Core engineering background: Python (Django / FastAPI) + React


• GenAI experience: 3-4+ years of hands-on, production-level experience, including Agentic AI


• Core stack: Python/Django, with React/Svelte on the front end.


• GCP/Azure is the primary cloud platform , it's nice to have.


• Location: Bangalore (or willing to relocate to Bangalore)

Key Responsibilities

GenAI Solution Development

• Build and deploy GenAI-powered features within real-world products, spanning backend (Python - Django/FastAPI) and frontend (React) layers.


• Design and implement RAG pipelines, including Embeddings, Vector databases, and Retrieval strategies.


• Integrate GenAI capabilities with backend systems via APIs and services.


• Build responsive, GenAI-integrated UI/UX components in React to surface AI-driven features to end users.

System & Solution Ownership

• Own GenAI solutions end-to-end, from design to production rollout across backend, frontend, and AI layers.


• Design RAG architectures and decide chunking strategies and retrieval approaches.


• Handle ambiguous requirements and convert them into working, shippable solutions.

Reliability, Quality & Performance

• Address latency, cost, and evaluation considerations in GenAI systems.


• Implement guardrails and safety mechanisms.


• Contribute to monitoring and basic operational readiness.

Agentic AI (Core Focus)

• Build and own agent-based workflows, including multi-step reasoning flows, tool/function calling, and orchestrated GenAI interactions.


• Work hands-on with agent frameworks to design and deploy production-grade agentic systems (deep research not required, but practical build experience expected).


• Mentor junior engineers working on GenAI components.


• Review GenAI-related code and designs, across both backend and frontend implementations.


• Collaborate closely with backend, frontend, data, and product teams.

Must-Have Skills

• Core stack: Python/Django, with React/Svelte on the front end.


• GCP/Azure is the primary cloud platform , it's nice to have.


• Strong engineering experience in Python (Django / FastAPI) and React.


• Hands-on experience building GenAI applications in production.


• Experience with RAG pipelines, Vector databases, LLM APIs, and Agentic AI (multi-step reasoning, tool/function calling, orchestration).


• Solid understanding of API design and backend integrations.


• Ability to reason about trade-offs in performance, cost, and reliability.

Nice-to-Have Skills

• Azure is good to have, as some requirements may involve Azure depending on the project.


• Familiarity with evaluation frameworks for GenAI.