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Experienced
About the role
This is a senior architecture role focused on designing and delivering end-to-end AI platforms for enterprise clients. You will work at the intersection of business and engineering, owning the technical design of advanced AI systems across classical machine learning, generative AI and agentic systems. It suits an experienced architect who can act as a lead authority in a domain such as agentic application design, AI security and trust, AI operations and observability, data and knowledge engineering, or model platforms and inference.
What you'll do
Translate business strategy into a technical vision and define non-functional requirements for performance, reliability and cost
Lead stakeholder workshops on technical feasibility, project scope and expectations
Drive technology selection and build-vs-buy decisions for AI platforms and foundation models
Architect model- and tool-agnostic multi-agent systems governed by an MCP Control Plane
Design and implement the Agent Registry and the AI Gateway for runtime policy enforcement
Design and implement a certification gate validating identity, policies and evaluation metrics before production
Design and abstract core agent services, including a memory service with semantic, episodic and procedural endpoints
Architect the end-to-end data pipeline covering ingestion, preprocessing and synchronization for fine-tuning and RAG
Design and implement the context layer spanning knowledge graphs, vector search and semantic retrieval
Architect foundation model adaptation strategies including cost- and performance-aware model routing
Design and prototype high-throughput, low-latency inferencing solutions using caching and request batching
Define security, governance and observability as centrally enforced, by-design controls
Architect a defense-in-depth security framework with per-agent identity, IAM/IAP binding and layered guardrails
Design and implement FinOps controls at the AI Gateway including token budgets, cost-center labeling and threshold alerts
Establish a system evaluation framework and instrument observability with OTel
Define and maintain the enterprise-wide AI reference architecture, reusable patterns and approved component library
Independently design, build and deliver proof-of-concept prototypes and foundational software components
Produce and own architecture artifacts such as blueprints, sequence diagrams, design specifications and ADRs
Mentor cross-functional engineering teams on architectural best practices and design patterns
Research and integrate emerging AI patterns, frameworks and technologies
Good to know
Based in Singapore
Full time position
Requirements
At least 5 years designing and deploying enterprise-grade advanced AI solutions using agentic, generative and classical AI/ML on at least one cloud vendor
At least 2 years in the agentic, LLM and generative AI space
At least 4 years of coding experience in Python
At least 2 years architecting and operationalizing LLM-driven application architecture patterns
At least 4 years in coding engineering, machine learning, deep learning and NLP solutions and applications
At least 4 years as a machine learning architect designing big data, machine learning and large-scale analytical engineering solutions
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