Data & AI - Artificial Intelligence Architect

Job description

Data & AI - Artificial Intelligence Architect CFGI is building its Data & AI practice in Singapore and is seeking a hands-on Artificial Intelligence Architect to own the solution architecture of client artificial intelligence builds and lead the team’s technical design. As the team’s lead architect and client-facing technical lead, you will design reference architectures — agent-first where open-ended reasoning or tool selection genuinely adds value, and conventional or deterministic designs where those are the better answer — set integration, security, and controls standards, own model and vendor strategy, and guide the engineering team in building solutions that are scalable, governed, and audit-ready. This is a Manager-level role based in Singapore, working with the Data & AI build team, including artificial intelligence engineers, a data engineer, and data scientists; CFGI’s APAC and global Data & AI, controls, and managed-services practices; and client Chief Technology Officers, Chief Data Officers, enterprise architects, and security and risk leaders. The role is hybrid in Singapore, with travel across Asia-Pacific expected for client work. Work-authorization sponsorship may be supported where required, subject to applicable eligibility and approval requirements. Healthcare and life sciences is the priority market, with delivery extending across CFGI’s other priority sectors, including technology and software, real estate and real-estate investment trusts, and industrials. Private equity will also serve as a cross-cutting channel across sectors. What you might expect: Own the solution architecture of the practice’s client artificial intelligence work and lead the team’s technical design from strategy and use-case definition through production deployment. Translate client strategies and use cases into build-ready reference architectures covering components, integration patterns, data flows, model choices, security controls, governance requirements, and delivery approaches. Determine when agentic architecture genuinely adds value over conventional or deterministic solutions and establish appropriate design patterns for each. Design reusable agent-first and enterprise artificial intelligence reference architectures, including multi-agent orchestration, agent-to-agent and Model Context Protocol tool layers, model gateways, retrieval and knowledge architectures, and integration patterns connecting artificial intelligence solutions to the client’s broader enterprise estate. Own model and vendor strategy and third-party model risk, including the approach to model selection across frontier and open-weight providers. Evaluate platforms, models, and tooling based on capability, cost, latency, context requirements, data residency, security, portability, and business needs. Design for model and vendor provenance, contractual controls, portability, and exit so that clients can make defensible technology decisions without unnecessary vendor lock-in. Embed security and controls into architecture from the outset, including prompt-injection defenses, least-privilege agent identity, tool authorization, sandboxing, human approval gates, data-leak prevention, memory integrity, data sovereignty, auditability, and evidence requirements. Design architectures capable of satisfying the governance, control, and audit expectations of regulated clients, boards, security teams, and regulators. Set and maintain the technical standard for the practice, including architecture principles, design patterns, non-functional requirements, technical assurance, and design-review processes across engagements. Review and assure engineering work while guiding artificial intelligence engineers, the data engineer, and data scientists toward consistent technical and architectural standards. Make critical build-versus-buy, platform, model-selection, integration, data, and architecture decisions across client engagements. Serve as the client-facing technical lead and run architecture and design sessions with Chief Technology Officers, Chief Data Officers, enterprise architects, security leaders, risk leaders, and other technical and executive stakeholders. Translate complex business problems into governed technical solutions and communicate architecture credibly to both technical teams and executive buyers. Contribute technical solutioning to proposals and pursuits by shaping the technical approach, delivery plan, architecture, and risk position alongside practice leadership. Build reusable practice assets, including reference architectures, architecture patterns, technical standards, methodologies, and accelerators. Mentor the engineering team and raise the technical bar as the Data & AI practice grows. Work with the Partner, Data & AI Innovation and, as the practice grows, the wider CFGI architecture community on enterprise-level technical and architecture decisions. What you must have: Approximately 6–10 years of experience in technical delivery, solution architecture, enterprise architecture, data architecture, cloud architecture, artificial intelligence architecture, and/or related technology consulting, including substantial experience architecting production artificial intelligence, data, or platform systems and leading technical work. Hands-on experience architecting production generative artificial intelligence and/or agentic systems, including orchestration, retrieval or knowledge architectures, model integration, enterprise integration patterns, and the transition of artificial intelligence solutions from design into production. Experience serving as a client-facing technical lead, translating business requirements into technical architecture and working directly with enterprise architects, technology leaders, security or risk stakeholders, and executive decision-makers. What sets you apart: Deep experience designing agentic and generative artificial intelligence systems, including multi-agent orchestration, agent-to-agent patterns, Model Context Protocol, model gateways, retrieval-augmented generation, vector architectures, knowledge graphs, prompt strategy, and system-level evaluation. Experience with agentic frameworks such as LangGraph, CrewAI, AutoGen, Microsoft Agent Framework, or comparable orchestration technologies. Strong understanding of frontier and open-weight model ecosystems and experience developing model-selection strategies based on capability, cost, latency, context window, data residency, security, and operational requirements. Experience evaluating proprietary model families such as Anthropic Claude, OpenAI GPT, and Google Gemini as well as open-weight models such as Meta Llama, Google Gemma, Microsoft Phi, Mistral, Cohere Command, or comparable technologies. Familiarity with models and artificial intelligence ecosystems relevant to Asia-Pacific markets, including Alibaba Qwen, DeepSeek, Zhipu AI GLM, Moonshot AI Kimi, 01.AI Yi, Naver HyperCLOVA X, LG EXAONE, ELYZA, AI Singapore SEA-LION, or similar regional and sovereign models. Deep architecture experience with one or more major cloud environments such as Microsoft Azure, Amazon Web Services, or Google Cloud Platform and their managed artificial intelligence and machine-learning services. Experience with Microsoft Foundry and Azure OpenAI, Amazon Bedrock, Google Vertex AI, or comparable managed artificial intelligence platforms. Understanding of sovereign and regional cloud environments relevant to Asia-Pacific data-residency requirements, including Alibaba Cloud, Tencent Cloud, Huawei Cloud, Naver Cloud, locally operated global-cloud environments, and/or self-hosted inference architectures. Experience designing integration architecture across application programming interfaces, event-streaming technologies, identity platforms, enterprise applications, and data environments. Working knowledge of modern data and machine-learning-operations architecture, including lakehouse architectures, semantic layers, observability, deployment, monitoring, and production operations. Experience designing security architecture for production artificial intelligence and agentic systems, including prompt-injection defense, tool authorization, least-privilege identity, sandboxing, human approval gates, memory integrity, auditability, data privacy, and data sovereignty. Experience incorporating artificial intelligence governance, model risk, control mapping, evidence, and audit requirements into enterprise architecture. Familiarity with major artificial intelligence governance frameworks and standards, including the European Union Artificial Intelligence Act, the United States National Institute of Standards and Technology Artificial Intelligence Risk Management Framework and Generative Artificial Intelligence Profile, ISO/IEC 42001, Singapore AI Verify, and Singapore’s Model Artificial Intelligence Governance Framework for Agentic Artificial Intelligence. Familiarity with emerging Asia-Pacific artificial intelligence regulatory and governance regimes, including relevant frameworks in Japan, South Korea, China, India, Australia, Singapore, and other Southeast Asian markets. Practical experience addressing data privacy, residency, and sovereignty requirements across multiple jurisdictions. Familiarity with privacy and data-protection regimes such as Singapore’s Personal Data Protection Act, Japan’s Act on the Protection of Personal Information, South Korea’s Personal Information Protection Act, India’s Digital Personal Data Protection Act, China’s Personal Information Protection Law and Data Security Law, Australia’s Privacy Act, and related Southeast Asian requirements. Experience designing controls and architecture jurisdiction by jurisdiction rather than retrofitting residency, sovereignty, privacy, and regulatory requirements after implementation. Demonstrated ability to make build-versus-buy decisions, evaluate third-party artificial intelligence vendors and models, assess model risk, and design for portability and vendor exit. Experience leading architecture and technical-design sessions and communicating complex technical decisions credibly to Chief Technology Officers, enterprise architects, security leaders, risk leaders, executive buyers, and other senior stakeholders. Experience contributing technical solutioning, architecture, delivery planning, and risk considerations to proposals, pursuits, and client presentations. Experience establishing architecture principles, reusable patterns, non-functional requirements, design-review processes, technical-assurance standards, or other architecture-governance mechanisms. Experience mentoring engineers, data professionals, or other technical team members and providing technical review and architecture guidance. Nice to have: Healthcare and life-sciences architecture experience involving clinical, regulatory, real-world-evidence, healthcare-data, or related systems. Experience with healthcare interoperability standards, clinical ontologies, and data models such as Fast Healthcare Interoperability Resources (FHIR), Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT), the Observational Medical Outcomes Partnership Common Data Model (OMOP CDM), or comparable healthcare standards. Experience designing artificial intelligence and data solutions within healthcare, life sciences, or another highly regulated environment. Office-of-the-Chief-Financial-Officer architecture experience involving artificial intelligence, data, financial close, reporting, controls, risk, or other finance-related use cases. TOGAF Enterprise Architecture Practitioner, ISO/IEC 42001 lead-implementer, or another relevant architecture, cloud, security, or artificial intelligence-governance credential. Published thought leadership related to artificial intelligence, architecture, data, security, or governance. Experience establishing or scaling an architecture capability within a growing consulting practice, technology organization, or artificial intelligence team. Who thrives here: A hands-on architect who is comfortable moving between enterprise-level architecture decisions and the practical realities of how engineers will build and operate the solution. Strong technical judgment with the ability to determine when agentic artificial intelligence adds real value and when a simpler deterministic architecture is the better answer. Excellent interpersonal, written, and verbal communication skills with the ability to build credibility across technical teams and executive stakeholders. Comfortable serving as a trusted technical advisor to Chief Technology Officers, Chief Data Officers, enterprise architects, security and risk leaders, and executive buyers. Strong analytical and structured problem-solving abilities with sound judgment in complex and rapidly evolving technology environments. Able to balance innovation with security, governance, regulatory, operational, and commercial considerations. Entrepreneurial, self-motivated, adaptable, ethical, and dependable. Comfortable operating in a small, fast-scaling team where roles are hands-on and individual contributions materially shape the practice. High energy with a commitment to exceptional client service, technical quality, team development, and practice growth. Take ownership of your career at CFGI: Help set the technical architecture of a Data & AI practice from its foundation. Work within a global firm with an established Data & Analytics practice, artificial intelligence capabilities, and a finance-and-controls heritage that supports governed and audit-ready artificial intelligence solutions. Work across sectors and across the full solution lifecycle, from reference architecture and technical design through governed build and production operation. Take a vendor-agnostic approach to solving client problems and select technologies based on what best fits the client’s requirements. Build reusable architectures, standards, patterns, and accelerators that influence how the practice delivers artificial intelligence solutions across Asia-Pacific. Work directly with senior client and CFGI stakeholders while maintaining meaningful influence over technical direction and solution design. Mentor a growing technical team and help establish the engineering and architecture standards that will support the practice as it scales. Develop toward broader senior technical-leadership opportunities as CFGI’s Asia-Pacific Data & AI practice grows. CFGI is an equal-opportunity employer and selects candidates based on job-related capability without regard to nationality, ethnicity, race, religion, gender, age, or any other protected characteristic. All qualified applicants are encouraged to apply. Work-authorization sponsorship may be supported but remains subject to Singapore Ministry of Manpower approval and applicable work-pass eligibility. Where required in connection with an Employment Pass application, the role will be advertised in accordance with applicable Singapore requirements. Data & AI - Artificial Intelligence Architect CFGI is building its Data & AI practice in Singapore and is seeking a hands-on Artificial Intelligence Architect to own the solution architecture of client artificial intelligence builds and lead the team’s technical design. As the team’s lead architect and client-facing technical lead, you will design reference architectures — agent-first where open-ended reasoning or tool selection genuinely adds value, and conventional or deterministic designs where those are the better answer — set integration, security, and controls standards, own model and vendor strategy, and guide the engineering team in building solutions that are scalable, governed, and audit-ready. This is a Manager-level role based in Singapore, working with the Data & AI build team, including artificial intelligence engineers, a data engineer, and data scientists; CFGI’s APAC and global Data & AI, controls, and managed-services practices; and client Chief Technology Officers, Chief Data Officers, enterprise architects, and security and risk leaders. The role is hybrid in Singapore, with travel across Asia-Pacific expected for client work. Work-authorization sponsorship may be supported where required, subject to applicable eligibility and approval requirements. Healthcare and life sciences is the priority market, with delivery extending across CFGI’s other priority sectors, including technology and software, real estate and real-estate investment trusts, and industrials. Private equity will also serve as a cross-cutting channel across sectors. What you might expect: Own the solution architecture of the practice’s client artificial intelligence work and lead the team’s technical design from strategy and use-case definition through production deployment. Translate client strategies and use cases into build-ready reference architectures covering components, integration patterns, data flows, model choices, security controls, governance requirements, and delivery approaches. Determine when agentic architecture genuinely adds value over conventional or deterministic solutions and establish appropriate design patterns for each. Design reusable agent-first and enterprise artificial intelligence reference architectures, including multi-agent orchestration, agent-to-agent and Model Context Protocol tool layers, model gateways, retrieval and knowledge architectures, and integration patterns connecting artificial intelligence solutions to the client’s broader enterprise estate. Own model and vendor strategy and third-party model risk, including the approach to model selection across frontier and open-weight providers. Evaluate platforms, models, and tooling based on capability, cost, latency, context requirements, data residency, security, portability, and business needs. Design for model and vendor provenance, contractual controls, portability, and exit so that clients can make defensible technology decisions without unnecessary vendor lock-in. Embed security and controls into architecture from the outset, including prompt-injection defenses, least-privilege agent identity, tool authorization, sandboxing, human approval gates, data-leak prevention, memory integrity, data sovereignty, auditability, and evidence requirements. Design architectures capable of satisfying the governance, control, and audit expectations of regulated clients, boards, security teams, and regulators. Set and maintain the technical standard for the practice, including architecture principles, design patterns, non-functional requirements, technical assurance, and design-review processes across engagements. Review and assure engineering work while guiding artificial intelligence engineers, the data engineer, and data scientists toward consistent technical and architectural standards. Make critical build-versus-buy, platform, model-selection, integration, data, and architecture decisions across client engagements. Serve as the client-facing technical lead and run architecture and design sessions with Chief Technology Officers, Chief Data Officers, enterprise architects, security leaders, risk leaders, and other technical and executive stakeholders. Translate complex business problems into governed technical solutions and communicate architecture credibly to both technical teams and executive buyers. Contribute technical solutioning to proposals and pursuits by shaping the technical approach, delivery plan, architecture, and risk position alongside practice leadership. Build reusable practice assets, including reference architectures, architecture patterns, technical standards, methodologies, and accelerators. Mentor the engineering team and raise the technical bar as the Data & AI practice grows. Work with the Partner, Data & AI Innovation and, as the practice grows, the wider CFGI architecture community on enterprise-level technical and architecture decisions. What you must have: Approximately 6–10 years of experience in technical delivery, solution architecture, enterprise architecture, data architecture, cloud architecture, artificial intelligence architecture, and/or related technology consulting, including substantial experience architecting production artificial intelligence, data, or platform systems and leading technical work. Hands-on experience architecting production generative artificial intelligence and/or agentic systems, including orchestration, retrieval or knowledge architectures, model integration, enterprise integration patterns, and the transition of artificial intelligence solutions from design into production. Experience serving as a client-facing technical lead, translating business requirements into technical architecture and working directly with enterprise architects, technology leaders, security or risk stakeholders, and executive decision-makers. What sets you apart: Deep experience designing agentic and generative artificial intelligence systems, including multi-agent orchestration, agent-to-agent patterns, Model Context Protocol, model gateways, retrieval-augmented generation, vector architectures, knowledge graphs, prompt strategy, and system-level evaluation. Experience with agentic frameworks such as LangGraph, CrewAI, AutoGen, Microsoft Agent Framework, or comparable orchestration technologies. Strong understanding of frontier and open-weight model ecosystems and experience developing model-selection strategies based on capability, cost, latency, context window, data residency, security, and operational requirements. Experience evaluating proprietary model families such as Anthropic Claude, OpenAI GPT, and Google Gemini as well as open-weight models such as Meta Llama, Google Gemma, Microsoft Phi, Mistral, Cohere Command, or comparable technologies. Familiarity with models and artificial intelligence ecosystems relevant to Asia-Pacific markets, including Alibaba Qwen, DeepSeek, Zhipu AI GLM, Moonshot AI Kimi, 01.AI Yi, Naver HyperCLOVA X, LG EXAONE, ELYZA, AI Singapore SEA-LION, or similar regional and sovereign models. Deep architecture experience with one or more major cloud environments such as Microsoft Azure, Amazon Web Services, or Google Cloud Platform and their managed artificial intelligence and machine-learning services. Experience with Microsoft Foundry and Azure OpenAI, Amazon Bedrock, Google Vertex AI, or comparable managed artificial intelligence platforms. Understanding of sovereign and regional cloud environments relevant to Asia-Pacific data-residency requirements, including Alibaba Cloud, Tencent Cloud, Huawei Cloud, Naver Cloud, locally operated global-cloud environments, and/or self-hosted inference architectures. Experience designing integration architecture across application programming interfaces, event-streaming technologies, identity platforms, enterprise applications, and data environments. Working knowledge of modern data and machine-learning-operations architecture, including lakehouse architectures, semantic layers, observability, deployment, monitoring, and production operations. Experience designing security architecture for production artificial intelligence and agentic systems, including prompt-injection defense, tool authorization, least-privilege identity, sandboxing, human approval gates, memory integrity, auditability, data privacy, and data sovereignty. Experience incorporating artificial intelligence governance, model risk, control mapping, evidence, and audit requirements into enterprise architecture. Familiarity with major artificial intelligence governance frameworks and standards, including the European Union Artificial Intelligence Act, the United States National Institute of Standards and Technology Artificial Intelligence Risk Management Framework and Generative Artificial Intelligence Profile, ISO/IEC 42001, Singapore AI Verify, and Singapore’s Model Artificial Intelligence Governance Framework for Agentic Artificial Intelligence. Familiarity with emerging Asia-Pacific artificial intelligence regulatory and governance regimes, including relevant frameworks in Japan, South Korea, China, India, Australia, Singapore, and other Southeast Asian markets. Practical experience addressing data privacy, residency, and sovereignty requirements across multiple jurisdictions. Familiarity with privacy and data-protection regimes such as Singapore’s Personal Data Protection Act, Japan’s Act on the Protection of Personal Information, South Korea’s Personal Information Protection Act, India’s Digital Personal Data Protection Act, China’s Personal Information Protection Law and Data Security Law, Australia’s Privacy Act, and related Southeast Asian requirements. Experience designing controls and architecture jurisdiction by jurisdiction rather than retrofitting residency, sovereignty, privacy, and regulatory requirements after implementation. Demonstrated ability to make build-versus-buy decisions, evaluate third-party artificial intelligence vendors and models, assess model risk, and design for portability and vendor exit. Experience leading architecture and technical-design sessions and communicating complex technical decisions credibly to Chief Technology Officers, enterprise architects, security leaders, risk leaders, executive buyers, and other senior stakeholders. Experience contributing technical solutioning, architecture, delivery planning, and risk considerations to proposals, pursuits, and client presentations. Experience establishing architecture principles, reusable patterns, non-functional requirements, design-review processes, technical-assurance standards, or other architecture-governance mechanisms. Experience mentoring engineers, data professionals, or other technical team members and providing technical review and architecture guidance. Nice to have: Healthcare and life-sciences architecture experience involving clinical, regulatory, real-world-evidence, healthcare-data, or related systems. Experience with healthcare interoperability standards, clinical ontologies, and data models such as Fast Healthcare Interoperability Resources (FHIR), Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT), the Observational Medical Outcomes Partnership Common Data Model (OMOP CDM), or comparable healthcare standards. Experience designing artificial intelligence and data solutions within healthcare, life sciences, or another highly regulated environment. Office-of-the-Chief-Financial-Officer architecture experience involving artificial intelligence, data, financial close, reporting, controls, risk, or other finance-related use cases. TOGAF Enterprise Architecture Practitioner, ISO/IEC 42001 lead-implementer, or another relevant architecture, cloud, security, or artificial intelligence-governance credential. Published thought leadership related to artificial intelligence, architecture, data, security, or governance. Experience establishing or scaling an architecture capability within a growing consulting practice, technology organization, or artificial intelligence team. Who thrives here: A hands-on architect who is comfortable moving between enterprise-level architecture decisions and the practical realities of how engineers will build and operate the solution. Strong technical judgment with the ability to determine when agentic artificial intelligence adds real value and when a simpler deterministic architecture is the better answer. Excellent interpersonal, written, and verbal communication skills with the ability to build credibility across technical teams and executive stakeholders. Comfortable serving as a trusted technical advisor to Chief Technology Officers, Chief Data Officers, enterprise architects, security and risk leaders, and executive buyers. Strong analytical and structured problem-solving abilities with sound judgment in complex and rapidly evolving technology environments. Able to balance innovation with security, governance, regulatory, operational, and commercial considerations. Entrepreneurial, self-motivated, adaptable, ethical, and dependable. Comfortable operating in a small, fast-scaling team where roles are hands-on and individual contributions materially shape the practice. High energy with a commitment to exceptional client service, technical quality, team development, and practice growth. Take ownership of your career at CFGI: Help set the technical architecture of a Data & AI practice from its foundation. Work within a global firm with an established Data & Analytics practice, artificial intelligence capabilities, and a finance-and-controls heritage that supports governed and audit-ready artificial intelligence solutions. Work across sectors and across the full solution lifecycle, from reference architecture and technical design through governed build and production operation. Take a vendor-agnostic approach to solving client problems and select technologies based on what best fits the client’s requirements. Build reusable architectures, standards, patterns, and accelerators that influence how the practice delivers artificial intelligence solutions across Asia-Pacific. Work directly with senior client and CFGI stakeholders while maintaining meaningful influence over technical direction and solution design. Mentor a growing technical team and help establish the engineering and architecture standards that will support the practice as it scales. Develop toward broader senior technical-leadership opportunities as CFGI’s Asia-Pacific Data & AI practice grows. CFGI is an equal-opportunity employer and selects candidates based on job-related capability without regard to nationality, ethnicity, race, religion, gender, age, or any other protected characteristic. All qualified applicants are encouraged to apply. Work-authorization sponsorship may be supported but remains subject to Singapore Ministry of Manpower approval and applicable work-pass eligibility. Where required in connection with an Employment Pass application, the role will be advertised in accordance with applicable Singapore requirements.