Principal AI Architect

Job Title: Principal AI Architect & Transformation Lead

GenAI | Agentic Systems | Enterprise Transformation

Lead discovery, architecture, and hands-on delivery of enterprise AI solutions. The role combines business transformation, GenAI architecture, agentic systems, platform engineering, and governance to produce measurable business outcomes.

Key Responsibilities

• Lead design-thinking and discovery workshops to identify workflow friction and high-value AI opportunities.
• Translate business challenges into prioritized AI roadmaps, solution architectures, and measurable outcomes.
• Design agentic workflows, multi-agent orchestration and context-aware systems.
• Architect memory patterns using short-term, long-term, episodic, and graph-based approaches.
• Design and build production-grade GenAI, RAG, Agentic RAG and tool-calling solutions.
• Create reusable accelerators, reference architectures, engineering standards, and implementation playbooks.
• Optimize context engineering, evaluation, model performance, reliability, latency, and inference cost.
• Design secure cloud-native platforms, APIs, microservices, integrations, CI/CD and observability.
• Embed Responsible AI, security, privacy and governance into solution design and delivery.
• Mentor engineering teams and build organizational capability in applied AI.

Required Skills

• Generative AI, LLM architecture, transformer concepts, RAG, and multi-agent systems.
• Hands-on experience with one or more frameworks: Semantic Kernel, LangGraph, AutoGen or CrewAI.
• Context engineering, prompt design, AI evaluation, observability and performance optimization.
• Knowledge graphs, ontologies, semantic layers, vector databases, and enterprise search.
• Expert Python development, API design, microservices and cloud-native engineering.
• CI/CD, automated testing, monitoring and production operations for AI systems.
• Azure AI Foundry, Azure OpenAI, Azure AI Search, Azure Functions, Microsoft Graph and Copilot Studio.
• Strong executive communication, facilitation, architecture leadership, and problem-solving.

Experience & Qualifications

• 8+ years in software engineering, solution architecture, platform engineering, or related discipline.
• 3+ years of architecting and deploying production GenAI or LLM solutions.
• Demonstrated experience working with business and executive stakeholders to deliver measurable value.
• Bachelor's or master's degree in Computer Science, Engineering or a related discipline, or equivalent practical experience.

Preferred Skills

• Experience creating enterprise AI platforms, copilots, reusable accelerators, or AI centers of excellence.
• Knowledge of enterprise architecture, Responsible AI, model lifecycle management and FinOps.
• Experience leading cross-functional transformation programmes and mentoring technical teams.

Success Measures

• AI solutions move from discovery to production with clear business outcomes.
• Reusable patterns reduce delivery time, risk, and duplication across use cases.
• AI platforms meet agreed standards for quality, security, governance, and cost.