Scope:
As an Enterprise Architect – Emerging Technologies & Innovation, you will drive the exploration, evaluation, and adoption of emerging technologies – with a primary focus on Artificial Intelligence (AI), Generative AI, and Agentic AI – across the enterprise technology landscape. You will lead proof-of-concept (POC) initiatives anchored on the Microsoft AI stack (Microsoft 365 Copilot, GitHub Copilot, Copilot Studio, and Copilot Cowork) and the Anthropic Claude ecosystem (Claude, Claude API, Claude Code), while maintaining the breadth to evaluate and apply learnings across other leading AI platforms and emerging technologies. You will partner closely with business and technology stakeholders to translate these capabilities into measurable business value and shape the organization’s innovation roadmap. Operating within the Enterprise Architecture function, you will set technical direction for AI adoption, establish reusable patterns and reference architectures, and collaborate across teams to deliver scalable, secure, and responsible AI-enabled solutions both on-prem and in the cloud. You will play a critical role in identifying high-value opportunities, de-risking adoption through structured experimentation, and accelerating the organization’s journey to becoming an AI-first enterprise.
What You’ll Do:
- Define and drive the enterprise vision and strategy for AI adoption and emerging technology innovation, aligned with the organization’s business goals and technology trends.
- Lead the design, execution, and evaluation of proof-of-concepts (POCs) across AI, Generative AI, Agentic AI, Machine Learning, and other emerging technologies; translate POC outcomes into pragmatic productionization roadmaps.
- Drive enterprise rollout and adoption of the Microsoft AI stack – Microsoft 365 Copilot, GitHub Copilot, Copilot Studio, and Copilot Cowork – including extensibility through Copilot agents, plugins, skills, and connectors.
- Architect solutions leveraging the Anthropic Claude ecosystem – Claude API for application integration and Claude Code for engineering productivity – and define when to apply Claude versus alternative models.
- Establish architectural standards, reference architectures, patterns, and guardrails for AI/ML and emerging-technology solutions, including responsible AI, model governance, and data ethics.
- Evaluate, benchmark, and recommend AI platforms, foundation models, vector databases, agent frameworks, and MLOps/LLMOps tooling – with the ability to compare Microsoft and Anthropic offerings against the broader market (OpenAI, Google Vertex AI, AWS Bedrock, open-source models).
- Partner with Data, Security, Infrastructure, and Application architecture teams to ensure AI initiatives integrate cleanly with enterprise data, identity (e.g., Entra ID), and security frameworks.
- Architect end-to-end solutions leveraging large language models (LLMs), retrieval-augmented generation (RAG), fine-tuning, and agentic workflows.
- Conduct vendor evaluations, technology assessments, and total-cost-of-ownership analyses for emerging technology investments; attend meetings with vendors and perform architecture and code reviews.
- Collaborate with business stakeholders to identify high-value AI use cases, prioritize the innovation pipeline, and define clear success metrics and KPIs.
- Develop frameworks and dashboards for measuring the impact, cost, and risk of AI and emerging-technology initiatives across the enterprise.
- Provide thought leadership and mentorship across the technology organization on emerging technologies, evangelizing adoption and upskilling engineering and architecture teams.
- Ensure compliance and governance with global and regional regulatory requirements (e.g., EU AI Act, data privacy laws), responsible AI principles, and internal policies.
- Stay current with the rapidly evolving landscape of AI, Generative AI, agentic systems, and other emerging technologies; bring external insight and industry best practices into the organization.
- Act as a liaison between innovation initiatives, technical teams, and senior management to communicate architectural decisions, trade-offs, and business impact.
What We’re Looking For:
- Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field; Master’s degree preferred.
- At least 10+ years of experience in technology roles with a strong focus on architecture, solutioning, and the adoption of emerging technologies.
- At least 3+ years of hands-on experience designing or delivering AI/ML or Generative AI solutions in an enterprise environment.
- Demonstrated hands-on experience with the Microsoft AI stack (Microsoft 365 Copilot, GitHub Copilot, Copilot Studio, Copilot Cowork) and/or the Anthropic Claude ecosystem, with the breadth to apply that experience to other AI platforms and emerging technologies as they evolve.
- Proven track record of leading proof-of-concepts (POCs) from ideation through evaluation, recommendation, and handover to production.
- Strong communication and stakeholder management skills, with the ability to translate complex technical concepts for business audiences.
Technical Skills:
- Primary – Microsoft AI Stack: Hands-on experience with Microsoft 365 Copilot, GitHub Copilot, Copilot Studio (including building custom Copilots, agents, skills, plugins, and connectors), and Copilot Cowork (Frontier program, autonomous task execution across M365). Familiarity with Work IQ, Microsoft Graph, Power Platform integration, and Entra ID for secure AI deployments.
- Primary – Anthropic Claude Ecosystem: Practical experience designing solutions on Claude via the Anthropic API and AWS Bedrock; familiarity with Claude Code for software engineering workflows and the Model Context Protocol (MCP) for tool and data integration.
- Broader AI/ML Foundations: Strong understanding of LLMs, foundation models, embeddings, vector databases (e.g., Azure AI Search, Pinecone, Weaviate, pgvector), Retrieval-Augmented Generation (RAG) architectures, prompt engineering, and fine-tuning techniques.
- Comparative Platform Knowledge: Ability to evaluate Microsoft and Anthropic offerings against the broader market – OpenAI, Google Vertex AI / Gemini, AWS Bedrock, Hugging Face, and leading open-source models – and recommend the right tool for each use case.
- Agentic AI and Tooling: Familiarity with agentic frameworks (e.g., Copilot Studio agents, LangChain, LangGraph, AutoGen, Semantic Kernel) and MLOps/LLMOps tooling (e.g., Azure ML, MLflow, LangSmith).
- Programming Awareness: Working knowledge of Python and common AI/ML libraries sufficient to evaluate POCs, review prototypes, and engage credibly with engineering teams – this is an architecture role, not a hands-on coding role.
- Cloud and Data Architecture: Deep experience with Microsoft Azure (preferred) and working knowledge of AWS and GCP; familiarity with modern data architectures including Microsoft Fabric, data lakes, lakehouses, and streaming pipelines.
- Responsible AI: Strong understanding of responsible AI principles – fairness, explainability, model governance, AI safety, and risk management – including Microsoft’s Responsible AI Standard and Anthropic’s safety practices.
- Integration: Knowledge of enterprise integration patterns, APIs, and middleware (e.g., MuleSoft, Boomi, Azure Logic Apps) to embed AI capabilities into existing enterprise applications.
Our Values
If you want to know the heart of a company, take a look at their values. Ours unite us. They are what drive our success – and the success of our customers. Does your heart beat like ours? Find out here: Core Values
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.