Lead AI Architect​/Strategist

This role is designed for a visionary technology leader who will define and accelerate enterprise AI transformation through innovative architecture and strategic execution.
You will lead the design of scalable AI solutions, enabling organizations to adopt Generative AI, Large Language Models, intelligent agents, and advanced analytics capabilities.
The position combines technical leadership, architecture expertise, and business alignment to create secure, impactful AI solutions.
You will collaborate with engineering, data, product, cybersecurity, and executive teams to establish AI roadmaps and implementation strategies.
This opportunity offers the chance to shape the future of AI adoption by building responsible, scalable, and mission-driven technology solutions.
You will work in an environment focused on innovation, continuous improvement, and solving complex challenges through emerging technologies.

• Define and execute AI architecture strategies, technical roadmaps, and modernization initiatives aligned with organizational priorities.
• Design scalable AI platforms and solutions leveraging Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, machine learning, and automation technologies.
• Architect intelligent AI systems integrating models, data platforms, enterprise applications, and APIs.
• Develop architecture standards and best practices for LLM applications, AI copilots, agentic workflows, knowledge retrieval systems, and data-driven decision solutions.
• Design and evaluate RAG architectures, including data ingestion pipelines, embeddings, vector search, retrieval strategies, and model orchestration.
• Lead assessments of emerging AI technologies, frameworks, and platforms to identify opportunities for innovation.
• Guide engineering and data teams from AI proof‑of‑concept development through production implementation.
• Establish AI governance practices supporting security, compliance, responsible AI principles, scalability, and operational excellence.
• Collaborate with software engineers, data scientists, product teams, cybersecurity teams, and enterprise architects to deliver AI-enabled solutions.
• Provide technical mentorship and leadership on AI architecture patterns, engineering practices, and implementation approaches.
• Communicate complex AI concepts and recommendations clearly to technical teams, business stakeholders, and executive audiences.
• Support innovation initiatives through prototypes, technical demonstrations, and enterprise AI transformation programs.

The ideal candidate is a strategic and hands‑on technology leader with deep expertise in AI architecture, enterprise systems, cloud platforms, and modern software engineering practices. This professional should be capable of bridging technical innovation with business objectives while delivering secure and scalable AI solutions.

• Bachelor’s degree in Computer Science, Information Technology, Engineering, Data Science, or a related technical field.
• 10+ years of experience in software engineering, enterprise architecture, solution architecture, data architecture, or technology transformation.
• 5+ years of experience designing and implementing AI/ML solutions, AI platforms, or intelligent automation solutions.
• Proven experience architecting enterprise‑scale technology solutions and distributed systems.
• Strong expertise in Generative AI, Large Language Models (LLMs), and AI application architectures.
• Hands‑on experience with AI technologies including Retrieval‑Augmented Generation (RAG), AI Agents, Agentic AI workflows, prompt engineering, vector databases, embeddings, model orchestration, and AI lifecycle management.
• Experience with cloud AI platforms such as Azure OpenAI, Azure AI Services, AWS Bedrock, or Google Vertex AI.
• Experience with modern AI frameworks and tools such as Lang Chain, Lang Graph, Llama Index, Semantic Kernel, or similar technologies.
• Strong programming experience with Python or other modern programming languages.
• Experience with data architecture, APIs, data pipelines, and enterprise system integrations.
• Understanding of MLOps and LLMOps practices, including monitoring,…