Role Overview

We are looking for a

hands-on GenAI Architect

to design and deliver

production-grade AI systems

. This role combines

architecture, engineering, and leadership

, with full ownership from concept to deployment.

Key Responsibilities

• Design end-to-end

Generative AI systems

(RAG, copilots, multi-agent workflows)

• Build and scale

LLM-powered applications

in production environments

• Define architecture across

data, APIs, orchestration, and infrastructure

• Implement

evaluation, observability, and LLMOps practices

• Ensure

performance, scalability, security, and cost optimization

• Lead technical decisions and

mentor engineering teams

• Work with stakeholders to translate business needs into AI solutions

Core Skills Required

• Strong experience in

Python (FastAPI, APIs, async systems)

• Hands-on with

RAG, vector databases, and agent frameworks

• Experience with

LLMs (OpenAI, Claude, Gemini, Llama, etc.)

• Cloud expertise:

AWS / Azure / GCP

• Solid understanding of

system design, distributed systems, and backend architecture

• Experience building

production AI systems (not just PoCs)

Not a Fit If

• Experience limited to

projects, demos, or hackathons

• Only

prompt engineering

without system ownership

• No exposure to

production deployment or scaling AI systems

What You’ll Build

• AI copilots for enterprise workflows
• RAG-based knowledge systems
• Multi-agent AI solutions
• Document intelligence pipelines
• AI-driven decision systems

Ideal Candidate

• Strong

architecture + coding + AI

combination

• Proven track record of

shipping production AI systems

• Ability to balance

quality, cost, and scalability