AI Architect

Responsibilities

• Defining and evolving WhiteTech’s AI architecture and long-term AI technology strategy.
• Designing production-grade AI and LLM-powered solutions integrated with existing fintech products and services.
• Architecting AI agents, conversational systems, intelligent workflows, and AI-assisted automation.
• Designing Retrieval-Augmented Generation (RAG) architectures, enterprise knowledge systems, and semantic search solutions.
• Selecting appropriate AI models, model providers, platforms, and infrastructure based on business, technical, security, latency, and cost requirements.
• Defining patterns for integrating LLMs and AI services into existing backend and microservice architectures.
• Designing scalable orchestration layers for prompts, tools, agents, APIs, models, and enterprise data sources.
• Establishing standards for prompt management, model routing, structured outputs, context management, and AI service integration.
• Defining AI evaluation frameworks, quality metrics, monitoring, observability, and feedback loops.
• Designing safeguards and guardrails to improve reliability, security, privacy, explainability, and responsible use of AI.

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