Senior AI Systems Architect 9DSC/SN)

Company description:

Singapore Technologies Engineering Ltd

Job description:

ST Engineering is a global technology, defence and engineering group with offices across Asia, Europe, the Middle East and the U.S., serving customers in more than 100 countries. The Group uses technology and innovation to solve real-world problems and improve lives through its diverse portfolio of businesses across the aerospace, smart city, defence and public security segments. Headquartered in Singapore, ST Engineering ranks among the largest companies listed on the Singapore Exchange.

Join our Cyber Team

We are an industry leader in cybersecurity with over two decades of experience, we deliver a holistic suite of trusted cybersecurity solutions to empower cyber resilience for government and ministries, critical infrastructure, and commercial enterprises. Backed by our indigenous capabilities and deep domain expertise, we offer robust cyber-secure products and services in cryptography, cybersecurity engineering, digital authentication, SCADA protection, audit and compliance. We specialise in the design and build of security operations centres for cybersecurity professionals and provide managed security services to strengthen the cybersecurity posture of our government and enterprise customers.

The role requires a forward-thinking AI Systems Architect who can bridge technical depth with enterprise-scale impact, driving the adoption of agentic AI within robust, secure, and scalable IT environments.

Responsibilities

Agentic AI Architecture & Systems Design

• Design and operationalize agentic AI systems within an enterprise IT and Service-Oriented Architecture (SOA) framework.
• Define system components, APIs, and interfaces for embedding agent-based intelligence into scalable, modular platforms.
• Ensure adaptability, reusability, and maintainability of agentic AI services across enterprise applications.

AI Workflow & Business Integration

• Collaborate with business and IT stakeholders to align agentic AI capabilities with strategic goals and operational workflows.
• Translate business requirements into intelligent agent-driven processes that optimize decision-making and automation.
• Conduct feasibility assessments and define KPIs for agent-enabled systems.

Data & Model Infrastructure

• Architect and manage the infrastructure supporting agentic AI workflows, including real-time data pipelines, feature stores, and model registries.
• Oversee the full lifecycle of AI agents—from model training and orchestration to deployment, monitoring, and iteration.
• Seamlessly integrate ML models, reasoning engines, and multi-agent systems into core IT and product platforms.

Scalability, Performance & Optimization

• Design systems to support distributed, high-performance, and real-time agentic AI processing.
• Optimize infrastructure for low-latency decision loops and efficient agent coordination.
• Balance performance, cost, and scalability across AI compute resources and workflows.

Collaboration & Leadership

• Partner with data engineers, software developers, MLOps, and DevOps teams to ensure robust integration and lifecycle management of intelligent agents.
• Define and enforce best practices for agent orchestration, CI/CD of AI systems, and live system monitoring.
• Provide strategic and technical leadership in the operational deployment of AI agents across the enterprise.

Requirements

Experience

• 8+ years in AI systems architecture, data science, or enterprise software engineering.
• Proven experience implementing AI/ML systems within SOA or cloud-native architectures.
• Hands-on experience integrating autonomous AI agents or models into enterprise products.

Technical Skills

• Proficiency with AI/ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn) and agentic system design.
• Advanced Python development skills; experience with deployment tools and container orchestration (e.g., Docker, Kubernetes).
• Deep knowledge of data pipelines, event-driven architectures (Kafka, Flink), and real-time AI processing.
• Experience with MLOps, model versioning, and observability tools in production environments.

Strategic & Analytical Thinking

• Ability to align agentic AI capabilities with business priorities and technical constraints.
• Skilled in conducting impact assessments, risk analyses, and designing AI-first processes.
• Strong problem-solving and communication skills across technical and non-technical audiences.

Preferred Qualifications

• Certifications in AI, Machine Learning, or Agent-Based Systems
• Experience with Large Language Models (LLMs), multi-agent orchestration frameworks, and cognitive architectures

Work location: Jurong East

Find out more:

ST Engineering believes in fostering a culture where team members are encouraged to overcome challenges, explore new ideas, and work together to succeed. We value individuals who are determined to push beyond the boundaries, and have a thirst for knowledge, continuous learning, and self-improvement.