Senior Solution Architect – Data & AI
Experience Level: Senior Executive (20+ years of experience)
Location: SINGAPORE
Role Overview
We are looking for a Senior Solution Architect – Data & AI to lead end-to-end architecture across presales and delivery. The role will involve client engagement, solution design, RFP/RFI responses, enterprise Data & AI architecture, and delivery governance.
Key Responsibilities
Presales & Client Solutioning
- Lead Data & AI solutioning for RFPs, RFIs, tenders, proposals and client presentations.
- Engage clients to understand business objectives, technical requirements, data maturity and AI opportunities.
- Translate business requirements into solution architecture, scope, estimates, roadmap, risks and dependencies.
- Develop practical and commercially viable solution options in collaboration with Sales, Account, Delivery and Technology Partners.
- Present proposed solutions and value propositions to senior client stakeholders.
Data & AI Architecture
- Design enterprise Data & AI solutions across cloud, hybrid and on-premises environments.
- Architect Data Lakes, Data Warehouses, Lakehouses, Analytics and Streaming platforms.
- Define architecture across data, AI, integration, infrastructure, security, operations and governance.
- Design data ingestion, ETL/ELT, transformation, metadata, lineage and data quality frameworks.
- Evaluate technologies based on scalability, performance, reliability, security and cost.
AI, GenAI & Advanced Analytics
- Design AI/ML and GenAI architectures, including LLMs, RAG, embeddings, vector databases and enterprise knowledge search.
- Assess AI use cases for feasibility, value, complexity, risk and operational impact.
- Define data pipelines and platform capabilities for AI workloads.
- Establish MLOps, ModelOps, model monitoring and AI lifecycle management approaches.
- Consider GPU infrastructure, latency, scalability, privacy, security and cost.
Governance, Security & Delivery
- Define Data Governance and AI Governance covering data ownership, metadata, lineage, quality, privacy, responsible AI, model risk and compliance.
- Work with Cyber, Risk, Compliance and Enterprise Architecture teams to validate security and governance controls.
- Act as the architecture lead during delivery and ensure implementation aligns with the approved solution.
- Guide Data Engineers, AI Engineers, Platform and Delivery teams through detailed design and implementation.
- Conduct architecture reviews, technical risk assessments and performance optimisation.
- Produce architecture diagrams, solution blueprints, technical specifications and documentation.
- Ensure a smooth transition from presales to delivery with clear scope, architecture and ownership.
Required Skills & Experience
- 15+ years of technology experience with strong experience in Solution Architecture, Data Architecture, AI Architecture, Enterprise Architecture or large-scale platform delivery.
- Proven experience in both presales solutioning and delivery architecture for enterprise Data & AI projects.
- Strong expertise in modern data platforms, cloud architecture, AI/ML, GenAI, analytics, integration and governance.
- Strong understanding of Data Lakes, Data Warehouses, Lakehouses, ETL/ELT, streaming, metadata, lineage and data quality.
- Experience with one or more platforms such as AWS, Azure, Google Cloud, Databricks, Snowflake, Microsoft Fabric, Synapse or BigQuery.
- Strong understanding of LLMs, RAG, embeddings, vector databases, MLOps/ModelOps and AI infrastructure.
- Knowledge of data security, privacy, responsible AI, AI governance and regulatory requirements.
- Strong experience in client engagement, stakeholder management, presentations and technical documentation.
- Commercially aware with experience in solution estimation, proposal development and implementation roadmaps.
- Experience in consulting, technology services or large-scale enterprise transformation is preferred.
- Experience with government/public-sector or large enterprise clients is advantageous.
- Strong analytical, problem-solving and communication skills with the ability to work across Sales, Architecture, Engineering, Cyber and Delivery teams.
- Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering, AI, Software Engineering or a related discipline.