AI Architect

Role Overview:

As a AI Architect - you will own the end-to-end implementation of scaling GenAI and Agentic AI use cases from PoC to large-scale production. You'll bring hands-on experience on LLM's ,SLMs, Agentic AI solutions for Payment, microservices , cloud , DevOps and system build experience.

Key Responsibilities:

- Architect the AI based solution for various AI Implementation, driving Agentic AI use cases from PoC to production.

- Lead the Business conversation and come up the AI Solution with various AI Technology

- Design, build, and deploy production-grade GenAI applications using Python (FastAPI), Java backend services, and React.js frontends.

- Develop LLM-powered systems including chatbots, voicebots, copilots, and agentic workflows.

- Fine-tuning (SFT, LoRA)

- Prompt engineering (ReAct, CoT, tool calling)

- Build multi-agent systems using frameworks such as LangGraph, ADK, Pydantic AI, supervisor-agent and hierarchical patterns.

- Ensure observability through logging, metrics, tracing, health checks, and drift monitoring.

- Optimize inference pipelines using GPU acceleration (multi-GPU setups) for performance and cost efficiency.

- Lead partner onboarding, technical documentation, and closure of InfoSec and risk processes.