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💼 Full-time🗓 2026-06-25

Core

Designing and maintaining the frontend and backend architecture and orchestration layer for AI systems, including retrieval-augmented generation and agentic systems.

Role type

Staff AI Architect

Builds

Scalable AI infrastructure, API endpoints, and tool-based reasoning agents for internal and customer-facing use cases.

Domain

AI Engineering, Backend Systems, LLM Orchestration

Deliverable

production ML models | infrastructure

Required skills

Python, FastAPI, LLM orchestration frameworks, vector databases, RAG patterns, Docker, CI/CD tooling, system architecture, technical strategy

Preferred skills

Full-stack development expertise, modular system design, mentoring senior engineers

Technologies

Python, FastAPI, LiteLLM, OpenAI, Anthropic, GitHub, Docker, GitHub Actions

Responsibilities

Architect and maintain Python-based services; Build and scale secure API endpoints; Implement orchestration logic and tool chaining; Optimize service performance and latency; Collaborate with cross-functional teams; Set up robust test coverage and CI pipelines; Drive technical strategy and roadmap; Mentor engineers on architecture and best practices

Seniority

Staff, hands-on IC with strategic leadership

Rewrite
## About the Role The AI Architect plays a critical role in our team. Working on both the frontend and backend architecture and orchestration layer for our AI systems, including retrieval-augmented generation systems, agentic systems, and tool integrations. ## Key Responsibilities - Architect and maintain Python-based services using FastAPI for internal and customer-facing AI use cases - Build and scale secure, well-structured API endpoints that interface with LLMs, vector stores, and agentic tools - Implement orchestration logic and tool chaining for advanced agent workflows - Optimize service performance and latency across AI infrastructure layers - Collaborate with frontend, AI, and devops teams to ensure system-wide reliability and observability - Set up robust test coverage and CI pipelines for backend services - Contribute to our modular architecture for tool-based reasoning agents - Stay current with emerging trends in AI engineering, LLM integrations, and scalable backend systems - Drive technical strategy and roadmap for AI infrastructure - Mentor and guide senior and mid-level engineers on architecture and best practices ## What You Will Bring To succeed in this role, you'll need deep full-stack development expertise, a strong understanding of modern architecture patterns, and a bias toward building modular, maintainable systems. ## Required Qualifications - 8+ years of experience as a full-stack engineer, with at least 3 years building scalable backend systems in Python - Strong knowledge of Flask or FastAPI for building and scaling production grade APIs - Experience with LLM orchestration frameworks (e.g., LiteLLM) and integrating OpenAI/Anthropic APIs - Familiarity with vector databases, embeddings, and RAG patterns - Experience building and maintaining infrastructure that integrates with frontends, CLIs, and external APIs - Comfortable with GitHub, Docker, and CI/CD tooling (e.g., GitHub Actions) - Proficiency in writing robust, tested, and well-documented backend code - Track record of leading technical initiatives
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