Role Overview: Architect and lead the development of the application layer for enterprise GenAI
solutions. Connect LLM backends to scalable frontends while managing API gateways and cloud
deployments.
Key Responsibilities
Application Architecture: Design scalable microservices that handle LLM requests, streaming
responses (Server-Sent Events), and context management.
Cloud & DevOps: Oversee the deployment of AI applications on AWS, Azure, or GCP.
Integrate CI/CD pipelines for AI software components.
Frontend & Backend Integration: Ensure seamless, low-latency integration between modern
frontends (React/Next.js) and Python/FastAPI backends running AI models.
Required Skills & Qualifications
- Tech Stack: Strong Python programming, familiarity with APIs (OpenAI, Anthropic), basic LangChain/LlamaIndex usage.
- Qualifications: Bachelor’s in CS or related field; 3–4 years software or data engineering experience with demonstrated exposure to LLM APIs.
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