Senior GenAI Engineer

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: 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).
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
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.
Exposure to cloud-native deployments.
Experience mentoring junior engineers

Work arrangement
No