Artificial Intelligence Engineer

Zemoso Technologies; Bengaluru; On-site; INR 4,200,000 - 6,500,000; Full time

Job summary

Zemoso Technologies seeks a Senior GenAI Engineer with 5–8 years of experience, proficient in Python (Django/FastAPI) and React, to build production‑grade GenAI solutions. This role is Bangalore‑based or relocatable and emphasizes ownership of end‑to‑end features, including backend, frontend and agentic AI workflows.

You will design RAG pipelines, integrate with APIs, mentor juniors, and collaborate with product and data teams.

Qualifications

• 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, 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.

Responsibilities

• Build and deploy GenAI-powered features within real-world products, spanning backend (Python — Django/FastAPI) and frontend (React).
• Design and implement RAG pipelines, including integration with backend systems via APIs and services.
• Build responsive, GenAI-integrated UI/UX components in React to surface AI-driven features to end users.
• Own GenAI solutions end-to-end, from design to production rollout — across backend, frontend, and AI layers.
• Design RAG architectures and decide how to handle ambiguous requirements and convert them into working solutions.
• Address latency, cost, and evaluation considerations in GenAI systems; implement guardrails and basic monitoring.
• Build and own agent-based workflows, including tool/function calling and orchestration; work with agent frameworks to deploy production-grade agentic systems.
• Mentor junior engineers; review GenAI-related code and designs; collaborate with backend, frontend, data and product teams.

Skills

Python (Django / FastAPI)

React

GenAI in production

Agentic AI / multi-step reasoning

RAG pipelines

Vector databases

LLM APIs

API design & backend integrations

Performance, cost, reliability trade‑o

Tools

Django

FastAPI

React

APIs

Job description

Senior GenAI Engineer (Python + React + Agentic AI)

Job Title - Senior GenAI Engineer

Overall experience: 5–8 years 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: 2-3+ years of hands‑on, production‑level experience, including Agentic AI
• 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:
• 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:
• 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:
• Tool/function calling
• 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).

Mentoring & Collaboration

• 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

• 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 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

• Familiarity with evaluation frameworks for GenAI.
• Exposure to cloud-native deployments.
• Experience mentoring junior engineers.