
Lead AI Solution Architect
- Singapore
- Permanent
- Full-time
- Design end-to-end AI solutions that are robust, scalable, and span data ingestion, model deployment, API orchestration, and business system integration across hybrid cloud and on-prem environments
- Architect and deliver solutions for the AI platform, encompassing Agentic AI, AI Workbench and Tooling, Model Garden, and AI Runtime environments.
- Lead solution blueprinting by translating business needs into technical architecture, including selecting appropriate tools, frameworks, and infrastructure for AI model development and operations
- Integrate AI capabilities with internal APIs, enterprise platforms and user-facing applications in IT and Networks including LLM-based and agentic workflows
- Ensure secure and compliant architecture in collaboration with cybersecurity and governance teams, embedding PDPA and enterprise policy requirements into designs
- Evaluate and recommend AI platforms and tools (e.g., Azure ML, AI Foundry, Databricks, open-source toolkits) based on enterprise goals and technical fit
- Collaborate with engineering and data teams to operationalize AI models, ensuring architectural alignment, scalability, and lifecycle support
- Define and enforce architectural standards, reusable design patterns, and reference implementations to streamline AI deployment across business units
- Provide technical leadership in prototyping, experimentation, vendor technology evaluations, and innovation pilots
- Stay updated on emerging AI technologies such as vector databases, context-aware agents, orchestration protocols (e.g. LangChain, LangGraph, MCP) and assess their applicability within the enterprise
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data, AI/ML, or related field.
- More than 5 years of experience in solution architecture or technical leadership roles, with a strong focus on AI platform integration and API-driven systems
- Proven expertise in designing and integrating end-to-end AI workflows, including data pipelines, model orchestration, and serving APIs across hybrid cloud environments
- Strong background in designing AI/ML systems, cloud-native architectures, and API ecosystems.
- Hands-on experience with cloud-based AI services such as Microsoft Azure ML, AI Foundry, AWS SageMaker, Bedrock, including model deployment, monitoring, and scaling.
- Experience with tools and frameworks such as LangChain, LangGraph, GraphRAG, Retrieval-Augmented Generation (RAG), MLflow, Kubeflow, and related AI/ML orchestration technologies.
- Proficient in API architecture and integration standards (REST, GraphQL, gRPC), with experience enabling secure and scalable interfaces between AI models and enterprise systems
- Strong understanding of containerization, virtual machines, microservices, and MLOps tools (e.g. MLflow, Kubeflow, Airflow, CI/CD pipelines)
- Demonstrated ability to evaluate and integrate new AI technologies, frameworks, and vendor solutions into enterprise environments
- Effective collaboration skills to work across data, platform, and cybersecurity teams, with a clear communication style to bridge business and technical stakeholders.
- Good internal (IT, Networks, business) and external (suppliers, government) stakeholders management skills
- Strong technical writing and presentation skills, with the ability to communicate complex concepts clearly to both technical and non-technical stakeholders.
- Proactive and fast learner with a strong drive to stay current on emerging technologies and industry trends.
- Full suite of health and wellness benefits
- Ongoing training and development programs
- Internal mobility opportunities