AI Systems Architect

Responsibilities

• Design AI-first system architecture for web and mobile applications
• Architect RAG pipelines using vector databases
• Define long-term memory, short-term memory, and contextual state systems
• Implement multi-agent AI systems and orchestration layers
• Select and implement vector databases such as Pinecone, Weaviate, Qdrant, Milvus, or Supabase
• Optimize embedding strategies and implement hybrid search
• Work with models including OpenAI, Anthropic, LLaMA, DeepSeek, and Qwen
• Build autonomous AI agents and tool-calling systems
• Integrate with n8n and LangGraph/LangChain style agent flows
• Build monitoring systems for hallucination detection and design guardrails
• Ensure security of AI pipelines and build scalable infrastructure using Docker and Kubernetes

Requirements

• 5+ years of software engineering experience
• 2+ years of building production AI systems
• Deep knowledge of vector embeddings, similarity search, and RAG architectures
• Proficiency in Python (mandatory)
• Experience with FastAPI and designing scalable APIs
• Knowledge of tokenization, context window optimization, and fine-tuning/LoRA concepts
• Experience with PostgreSQL and pgvector
• Experience designing distributed systems, microservices, and event-driven architecture
• Experience deploying LLM systems in production