AI Architect

Design reusable patterns for Agentic AI systems including RAG, Multi-Agent Orchestration, and Human-in-the-loop systems

Define how different agents communicate, share state, and hand off tasks to one another

Architect long-term and episodic memory layers using Vector Databases, embedding pipelines, and knowledge graphs

Decide when to use high-reasoning models vs. worker models to optimise cost and performance

Predict and control token usage architect systems with semantic caching to prevent redundant LLM spend

Set architectural standards for explainability, auditability, and guardrails to prevent hallucinations and bias

Ensure data governance, privacy compliance, and responsible AI practices across all systems

AI Infrastructure & MLOps

Design scalable AI infrastructure including model serving, inference architecture, AI microservices, and APIs

Architect distributed systems supporting AI workloads ...