Senior Artificial Intelligence Architect

Associate Director - Senior AI Architect

Job Description – Senior AI Architect

Job Title: Senior AI Architect
Grade: Associate Director (B grade) (Individual contributor role)
Function: Member-Firm technology Services – Technology Enablement & Operations (MFT-TEO)
Reports to: Head of Technology Enablement & Operations (TEO)
Framework Alignment: SFIA Level 6 – Initiate, Influence

 

Purpose of the Role

The Senior AI Architect is responsible for shaping, designing, and leading the development of enterprise-grade Artificial Intelligence (AI) solutions leveraging large language models (LLMs), retrieval-augmented generation (RAG), and agentic AI frameworks.
This role defines the AI architecture strategy, ensures alignment with enterprise technology principles, and provides leadership across multidisciplinary teams to deliver scalable, ethical, and innovative AI solutions within the Azure ecosystem.

 

Impact

• Drives the firm’s AI architecture vision, ensuring alignment to business and digital transformation goals.
• Leads the translation of emerging AI technologies into practical, scalable, and compliant enterprise applications.
• Influences senior stakeholders and technology forums to embed responsible AI principles and architectural standards.
• Mentors and uplifts engineering and data science teams, building organizational capability in AI engineering and governance.

 

Key Accountabilities

1. Solution Architecture (SFIA: ARCH – Level 6)

• Lead the design and governance of AI architectures across business domains.
• Define reusable patterns, reference architectures, and standards for AI application and data integration within Azure.
• Ensure architectures are secure, compliant, and optimized for scalability and performance.

 

2. Artificial Intelligence Development (SFIA: AIDV – Level 6)

• Direct the end-to-end design and deployment of intelligent systems using LLMs (e.g., OpenAI, Gemini, Mistral).
• Integrate agentic AI frameworks (e.g., LangGraph, CrewAI, AutoGen) to enable autonomous and semi-autonomous capabilities.
• Oversee model evaluation, prompt engineering, and continuous optimization for production-grade solutions.

 

3. Machine Learning and Data Science (SFIA: MLNG – Level 6, DATM – Level 6)

• Lead development of machine learning models and pipelines for NLP, predictive analytics, and pattern discovery.
• Define robust data engineering and governance standards to support AI model reliability and explainability.
• Ensure MLOps best practices for versioning, monitoring, and retraining of AI workloads.

 

4. Technology Strategy and Planning (SFIA: TECH – Level 6)

• Shape and maintain the AI technology roadmap aligned with enterprise digital strategy.
• Advise leadership on emerging technologies, frameworks, and trends in generative and autonomous AI.
• Contribute to enterprise-level technology policies, AI governance, and innovation principles.

 

5. Innovation and Research (SFIA: INAS – Level 6, RLMT – Level 5/6)

• Drive experimentation with emerging AI tools, frameworks, and architectures.
• Lead applied research initiatives in generative and agentic AI to enhance business capabilities.
• Translate successful proofs-of-concept into production-ready enterprise solutions.

 

6. Professional Leadership and Collaboration (SFIA Core Attributes – Level 6)

• Provide architectural mentorship and direction to software, data, and ML engineering teams.
• Influence multiple programmes and technology platforms through expert guidance.
• Communicate complex AI concepts to executive audiences, ensuring alignment between technical design and business value.

Expected Outcomes

• Enterprise AI solutions that are secure, scalable, and compliant with organizational governance.
• Established reusable architectural patterns and frameworks for AI delivery.
• Strengthened AI capability and awareness across engineering and business teams.
• Demonstrable contribution to the firm’s innovation and digital transformation agenda.

 

Required Experience & Skills

• 8+ years in enterprise solution architecture and/or technology design, including 3+ years hands-on leading AI/ML systems.
• Proven expertise in LLMs, RAG, agentic AI, and cloud-native solution architecture (Azure preferred).
• Strong knowledge of data science and ML techniques, including model evaluation and feature engineering.
• Deep understanding of CI/CD, DevOps/MLOps, and integration of AI workloads in enterprise environments.
• Demonstrated ability to influence senior stakeholders, mentor teams, and shape technology strategy.
• Excellent communication skills with the ability to convey complex AI concepts to both technical and business audiences.

 

Behavioural Competencies

• Strategic thinker with a focus on innovation and long-term technology outcomes.
• Confident communicator capable of influencing at senior levels.
• Strong collaborator with cross-functional leadership ability.
• Committed to ethical and responsible AI practices.
• Demonstrates continuous learning and thought leadership in AI technologies.

Experience Level

Mid Level