As an AI Architect, you will design and guide strategies for scalable, compliant, and cost‐efficient AI solutions across hybrid environments. You will combine frontier models (Azure OpenAI/Gemini) with small language models and edge inference to build advanced agentic AI systems that transform business operations.
You will work closely with senior technology and business leaders, define best practices, and lead complex AI architectures. This role requires strong hands‐on expertise in modern AI technologies (OpenAI, NVIDIA, Google, Microsoft, AWS) along with strategic business insight to serve as a trusted technical advisor.
Core Qualification:
* Enterprise Experience: 8–10+ years in technical leadership, with a strong background in both software engineering and enterprise-scale cloud architecture.
* Cloud Expertise: Architectural expertise with one primary cloud platform (Azure, GCP, or AWS) and hands-on familiarity with at least one other.
* GenAI & LLM Depth: Demonstrated experience architecting and guiding solutions using GenAI platforms (e.g., Azure OpenAI, Vertex AI, or AWS Bedrock).
* Model Fine-tuning: Experience with instruction tuning or fine-tuning strategies for LLMs.
* Leadership & Advisory Skills: Exceptional communication skills with demonstrated experience advising senior stakeholders (Director/C-Level) on technical strategy, roadmaps, and governance.
Preferred Qualifications
* Multi-Agent Systems: Deep understanding of, and experience designing or prototyping, advanced multi-agent systems (e.g., task decomposition, collaborative agents).
* Multi-Cloud Experience: hands-on architectural expertise across all three major clouds (Azure, AWS, GCP).
* GenAI Ops & Governance: Hands-on experience with GenAI Ops tooling. Familiarity with AI governance frameworks (NIST AI RMF, ISO 42001) and their practical application. And AI FinOps & Model Routing
* Framework Expertise: Hands-on development experience with one or more orchestration frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel).
* Thought Leadership & Open Source: Published work (whitepapers, patents), conference speaking engagements, or active contributions to relevant open-source projects.
* Certifications: Professional-level cloud certifications (e.g., Azure Solutions Architect Expert, AWS Solutions Architect Professional, GCP Professional Cloud Architect).
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