The AI Architect is responsible for defining the long-term technical vision for how AI is designed, structured, and scaled across the organization. Beyond building individual solutions, you will establish reusable patterns, reference architectures, and design principles that enable teams to build AI systems consistently, reliably, and at speed

Key Responsibilities & Skills

Architectural Design & Pattern Thinking

• Design and deliver standard AI system blue prints such as agentic loops, RAG pipelines, human-in-the-loop systems, and multi-modal inputs which are packaged as internal platforms, SDKs, and pattern libraries that teams adopt and build on rather than reinvent from scratch.

• Design for longevity, making architectural choices that age well and accumulate minimal technical debt over time

• Map unstructured business problems to AI-native solutions not just fitting known tools to familiar patterns

• Run discovery workshops or design sprints to surface the right AI approach before committing to a solution

Governance & Standards

• Define AI governance standards: model versioning policies, prompt lifecycle management, evaluation cadence, and deprecation strategies. Establish AI design principles across the organization guardrails, quality bars, and architectural constraints that apply to all AI products

• Design long-lived evaluation frameworks golden datasets and regression benchmarks that track quality over months and years, not just at launch

• Architect feedback loops that make AI systems self-improving over time through RLHF (Reinforcement Learning from Human Feedback), preference data collection, or active learning

• Translate multi-year business strategy into a phased AI architecture roadmap

Soft Skills & Experience

• Systems thinker sees how decisions made today shape the architecture two years from now

• Storyteller communicates complex architecture in a way that excites and aligns stakeholders, not just informs them

• 8–12+ years of overall engineering experience, with at least 3 years in AI/ML architecture

• Portfolio of AI systems that have run in production for 1+ years not just launched, but maintained and evolved

• Experience designing AI solutions that span multiple teams or business units