Lead Systems Engineer (Application Security Architect)

Singapore Airlines • SG • 2d ago

Job Description

The successful candidate will be a part of the Information Technology Division.

Key Responsibilities

Application Security Reviews and Threat Modelling

Lead security architecture reviews and threat modelling for assigned applications, platforms and technology initiatives, translating threats into practical design recommendations.
Assess authentication and authorization flows, including OAuth 2.0, OpenID Connect and JWT-based implementations.
Review AI deployment architectures, including retrieval-augmented generation (RAG), Model Context Protocol (MCP) integrations and agent workflows, working with specialists where required.
Help improve existing AI-enabled threat modelling capabilities and contribute to pilots that support cybersecurity delivery.
Provide technical guidance and mentoring to security consultants and engineering teams.
Embed security-by-design practices into development workflows through reusable guidance, design patterns and early engagement with delivery teams.
Support adoption of security tooling and report meaningful measures of coverage, remediation and developer engagement.
Help revitalise the Security Champions programme through practical training, knowledge sharing and support.
Contribute to security architecture standards and decisions across relevant business and technology domains.

Enterprise and Identity Security Architecture

Design and review identity integration patterns for hybrid and multi-cloud environments, covering human users, workloads and service identities.
Contribute to identity governance initiatives, including access lifecycle management, least privilege and access reviews.
Support identity integration for AI systems and automated workflows, including credential handling, delegated access and authorization boundaries.
Work with platform and DevOps engineering teams to establish secure infrastructure patterns and reusable technology foundations.
Build trusted relationships with stakeholders, explaining security trade-offs and helping teams implement proportionate controls.

Agentic and Generative AI Security

Contribute to security blueprints and guardrails for generative AI deployments within the organisation’s AI risk framework.
Assess risks in AI applications, including prompt injection, sensitive data exposure, excessive permissions and unsafe tool use.
Help design and implement authentication and authorization controls for AI agents and MCP integrations.
Partner with AI, engineering and risk teams to implement appropriate monitoring, logging and security controls throughout the AI application lifecycle.

Requirements

Bachelor’s degree in computer science, engineering or a related field, or equivalent practical experience.
5+ years of relevant experience across software engineering, solution architecture or application security.
Practical experience in application security architecture reviews and threat modelling, with the ability to translate findings into implementable engineering changes.
Experience delivering security or architecture improvements involving multiple stakeholders.
Strong understanding of application security principles, including OWASP guidance, secure coding, API security and authentication and authorization.
Experience integrating or using security tooling within development workflows, including SAST, DAST, software composition analysis, container scanning and secrets management.
Working knowledge of cloud security and identity patterns in AWS, Azure or comparable environments.
Practical exposure to securing AI-enabled applications, with familiarity in areas such as LLMs, RAG, MCP or agentic AI. Deep expertise across all these areas is not required.
Strong communication skills and the ability to explain security risks, discuss trade-offs and work constructively with technical and business stakeholders.
Experience in the following areas would be beneficial:
- Experience supporting a Security Champions programme.
- Experience implementing reusable security patterns, developer guidance or security automation.
- Exposure to identity governance, workload identity or authorization for AI agents.
- Relevant certifications, such as GIAC/SANS, AWS or Azure security certifications.