Enterprise Data & AI Architect

We are seeking an experienced Enterprise Data & AI Architect to lead the design, governance, and delivery of enterprise-grade AI and data platforms for our customers across the region.

This role is ideal for a senior architect with strong consulting and enterprise services experience who can bridge business transformation objectives with scalable AI solution architectures. You will work closely with customers, business consultants, AI engineers, cloud teams, and delivery stakeholders to shape modern AI platforms leveraging Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), intelligent agents, machine learning pipelines, and enterprise data ecosystems.

The successful candidate will play a critical role in both pre-sales engagements and solution delivery, ensuring architectures are scalable, secure, compliant, and aligned with enterprise transformation goals.

Key Responsibilities

1. Solution Architecture
   . Design and govern end-to-end enterprise AI architectures, including:
   . Large Language Model (LLM) solutions
   . Retrieval-Augmented Generation (RAG)
   . AI agents and autonomous workflows
   . Machine Learning (ML) pipelines
   . Enterprise data platforms and analytics ecosystems
   . Define scalable data integration patterns across structured and unstructured data sources.
   . Architect cloud-native and hybrid infrastructure environments to support resilient, high-performance AI workloads.
   . Design secure, scalable, and modular AI platforms aligned with enterprise architecture standards.
   . Ensure architecture compliance with enterprise security, privacy, governance, and regulatory requirements.
   . Collaborate with engineering and delivery teams to guide implementation and deployment strategies.
2. Pre-Sales & Customer Engagement
   . Engage customers in discovery workshops to understand business challenges, technical landscapes, and transformation objectives.
   . Assess technical feasibility and architecture readiness for AI and data initiatives.
   . Facilitate architecture and solution design workshops with customer stakeholders.
   . Lead and contribute to RFP/RFI responses with compelling technical narratives and scalable solution designs.
   . Develop solution blueprints, architecture diagrams, and technical proposals.
   . Present and articulate solution architectures to CIOs, CTOs, enterprise architects, and business executives.
   . Translate complex technical concepts into clear business outcomes and transformation value.
3. Technical Governance & Standards
   . Define and maintain enterprise AI reference architectures and target-state blueprints.
   . Develop reusable frameworks, accelerators, architecture patterns, and implementation standards.
   . Establish best practices across:
   . Model selection and evaluation
   . Prompt engineering and orchestration
   . Vector databases and retrieval strategies
   . AI application integration patterns
   . Deployment, monitoring, and lifecycle management (MLOps / LLMOps)
   . Ensure solutions align with responsible AI, ethical AI, governance, and compliance principles.
   . Provide architecture governance and technical oversight throughout project delivery lifecycles.
   . Mentor engineering and consulting teams on enterprise AI architecture best practices.

Requirements

Experience & Background
. Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or related field.
. 10+ years of experience in enterprise architecture, cloud architecture, AI/ML engineering, or data platform design.
. Proven experience designing enterprise-scale AI and data solutions in consulting, system integration, telecom, cloud, or managed services environments.
. Strong experience with cloud platforms such as:
. Microsoft Azure
. Amazon Web Services (AWS)
. Google Cloud Platform (GCP)
. Hands-on experience with Generative AI and LLM ecosystems.
. Experience architecting RAG pipelines, vector search, AI orchestration frameworks, and enterprise data integrations.
. Strong understanding of enterprise security, governance, and compliance requirements.

Technical Skills

Strong knowledge in:
. Generative AI and LLM architectures
. RAG design patterns and vector databases
. AI agents and orchestration frameworks
. Enterprise integration architecture
. Data engineering and analytics platforms
. API and microservices architecture
. Cloud-native architecture and Kubernetes
. MLOps / LLMOps frameworks and deployment pipelines
. Security architecture and identity/access management
. Hybrid cloud and enterprise infrastructure design

Preferred Qualifications
. Experience with enterprise AI governance and responsible AI frameworks.
. Experience with telecom, financial services, government, or large enterprise environments.
. Familiarity with AI ecosystem technologies such as:
. LangChain
. Semantic Kernel
. OpenAI ecosystem
. Vector databases
. MLFlow
. Databricks
. Cloud and architecture certifications preferred.
. Strong consulting, stakeholder management, and executive communication skills.

Key Competencies
. Strategic and systems thinking mindset
. Strong customer-facing consulting capability
. Excellent communication and presentation skills
. Ability to influence senior technical and business stakeholders
. Strong problem-solving and architecture governance skills
. Ability to work across multidisciplinary regional teams