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 lo