Zemoso Technologies
Senior GenAI Engineer (Python + React + Agentic AI)
Skills
1 month ago
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Important information
Contract type:
Permanent
Location:
Bengaluru, Karnataka, India
Work mode:
Onsite
Published on:
9 September 2026
What they need
Hiring JD — 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
- 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
- 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
- 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
- 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.
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