Sr. GenAI Engineer

Zemoso Technologies; Bengaluru; On-site; INR 3,500,000 - 6,000,000; Full time

Benefits offered by this job

Relocation assistance

Learning & development stipend

Job summary

Zemoso Technologies is seeking a Senior GenAI Engineer in Bengaluru who will build and deploy GenAI features across backend, frontend, and AI layers. You will design RAG architectures, orchestrate agentic workflows, and mentor junior engineers while collaborating with cross‑functional teams.

This role emphasizes practical build experience with GenAI in production and strong Python APIs. Ideal candidates have 5–8 years of experience, deep Python backend skills, and hands‑on GenAI expertise

Qualifications

• Proficient in Python backend frameworks (Django / FastAPI).
• Hands-on GenAI in production environments.
• Experience with agentic AI, tool calling and orchestration.

Responsibilities

• Build and deploy GenAI‑powered features in real products.
• Design and implement RAG pipelines for production use.
• Integrate GenAI with backend systems via APIs and services.
• Develop GenAI‑driven UI/UX components in React for surface features.
• Own end‑to‑end GenAI solutions from design to production rollout.
• Collaborate with backend, frontend, data, and product teams; mentor juniors.

Skills

Python Django FastAPI

GenAI production

Agentic AI

API design

Backend integrations

Job description

Location: Bangalore (or willing 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

frontend), working with agentic AI workflows, and mentoring junior engineers while handling

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)
• GenAI experience: 2-3+ years of hands‑on, production‑level experience, including Agentic AI.

Key Responsibilities

GenAI Solution Development

• Build and deploy GenAI‑powered features within real‑world products, spanning backend (Python — Django/FastAPI)
• 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).
• 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)
• Hands‑on experience building GenAI applications in production.
• Experience with:
  • 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.