Senior GenAI Engineer

Zemoso Technologies; Bengaluru; Sur place; INR 4 200 000 - 6 500 000; Plein temps

Résumé du poste

Zemoso Technologies in Bengaluru seeks a Senior GenAI Engineer to own end-to-end GenAI features, from backend to frontend, including agentic AI workflows. You will mentor peers, design RAG pipelines, and apply production-grade patterns in Python (Django/FastAPI) and React/Svelte while working with GCP/Azure.

Relocation to Bangalore or candidate willing to move is preferred; strong full-stack footing and hands-on GenAI delivery are essential.

Qualifications

• 5–8 years of overall software engineering experience.
• Hands-on GenAI production experience (3–4+ years).
• Proficient in Python (Django/FastAPI) and React/Svelte.
• Experience designing RAG pipelines and vector databases.
• Experience with cloud platforms (GCP/Azure).

Responsabilités

• Build and deploy GenAI-powered features across backend and frontend.
• Design and implement RAG architectures and retrieval strategies.
• Own GenAI solutions end-to-end from design to production.
• Mentor junior engineers and review GenAI-related work.
• Collaborate with backend, frontend, data and product teams.

Connaissances

Python

Django

React

GenAI

Agentic AI

RAG pipelines

LLM APIs

API design

Performance & reliability

Outils

FastAPI

Svelte

Django

React

Vector databases

Description du poste

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.