- Company Name
- Queen Square Recruitment
- Job Title
- Enterprise Architect
- Job Description
-
**Job Title**
Enterprise Architect (Agentic AI Implementation)
**Role Summary**
Lead the design and delivery of enterprise‑wide architectures for autonomous AI agents and generative AI solutions. Develop a strategic AI architecture vision, align it with digital transformation goals, and ensure scalable, secure, and ethically governed AI deployments across the organization. Collaborate with executive leadership, data scientists, engineers, and business stakeholders to translate high‑level objectives into actionable architectures.
**Expectations**
- 15+ years of IT experience, with 5+ years in enterprise architecture and 3+ years focused on AI/ML.
- Proven expertise in cloud‑native enterprise architecture (Microsoft Azure preferred).
- Hands‑on experience building and managing agentic AI systems, LLMs, and Python‑based frameworks (LangChain, AutoGen).
- Deep understanding of EA frameworks (TOGAF, Zachman) and MLOps, data governance, and security architectures.
- Strong stakeholder management and communication skills; capable of influencing decision‑makers at all levels.
**Key Responsibilities**
1. **AI Strategy & Roadmap** – Own the enterprise AI architecture vision and develop a roadmap aligned with long‑term digital goals.
2. **Architectural Design & Governance** – Design scalable, secure, and resilient architectures for agentic AI; establish governance around agent lifecycle, observability, interoperability, and compliance.
3. **Technology Evaluation** – Assess and recommend AI platforms and frameworks (LangChain, AutoGen, Azure AI Studio/Foundry, Databricks, etc.) for performance and scalability.
4. **Implementation Leadership** – Guide teams through design‑to‑deployment phases, overseeing AIOps, LLMOps, and agile practices to ensure smooth integration and production rollout.
5. **Data & Integration** – Collaborate with data teams to build robust pipelines and integrate AI solutions with enterprise systems (e.g., SAP, Salesforce, cloud‑native platforms).
6. **Security, Ethics & Compliance** – Embed responsible AI principles and enforce data privacy, security, and global AI governance standards.
7. **Cross‑Functional Collaboration** – Partner with business and technical stakeholders to translate strategic goals into actionable solutions and drive organizational adoption.
8. **Innovation & Research** – Stay current on agentic and generative AI trends, identifying opportunities for innovation and value creation.
**Required Skills**
- Enterprise and cloud‑native architecture (Azure).
- Agentic AI, LLMs, Python, LangChain, AutoGen.
- MLOps, data governance, security architecture.
- TOGAF/Zachman expertise.
- Strong stakeholder management and executive communication.
- Agile project leadership.
**Required Education & Certifications**
- Bachelor’s or Master’s degree in Computer Science, Information Systems, or related field (or equivalent experience).
- TOGAF certification (or equivalent EA framework).
- Microsoft Certified: Azure Solutions Architect Expert (preferred).
- Additional AI/ML certifications (e.g., Azure AI Engineer, TensorFlow, or similar) are desirable.