21 hours ago
Singapore, SingaporeStaff+
Responsibilities
- Define end-to-end solution architecture for one or more enterprise AI Value Pools.
- Lead multidisciplinary squads delivering scalable, secure, reusable, and production-ready AI solutions.
- Align AI solutions with enterprise architecture, security requirements, governance standards, approved platforms, and technical frameworks.
- Design integrations across data sources, enterprise platforms, legacy systems, and business applications.
- Ensure solutions address scalability, reliability, observability, maintainability, and operational readiness from prototype through Day 2 support.
- Lead technical alignment among business stakeholders, Product Owners, AI engineers, software developers, data teams, platform teams, IT, and network domains.
- Evaluate emerging AI technologies and vendor solutions while managing architectural deviations and technical debt.
- Establish technical direction, govern architectural quality, mentor Solution Architects, and promote reusable design patterns and engineering best practices.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data, AI/ML, or a related field.
- 5 to 10 years of experience in solution architecture or technical leadership, focused on AI platform integration and API-driven systems.
- Expertise designing, reviewing, and approving end-to-end AI workflows, including data pipelines, model orchestration, and serving APIs across hybrid cloud environments.
- Experience leading and managing software engineering and AI solution delivery teams.
- Strong background in AI/ML systems, cloud-native architectures, API ecosystems, and production-grade software architecture.
- Hands-on experience with Microsoft Azure ML, AI Foundry, AWS SageMaker, and Bedrock, including model deployment, monitoring, and scaling.
- Experience with LangChain, LangGraph, GraphRAG, Retrieval-Augmented Generation, MLflow, Kubeflow, and related AI/ML orchestration technologies.
- Proficiency in REST, GraphQL, and gRPC API architecture and integration standards.
- Understanding of containerization, virtual machines, microservices, and MLOps tooling including MLflow, Kubeflow, and Airflow.
- Ability to evaluate and integrate new AI technologies, frameworks, and vendor solutions into enterprise environments.
- Strong stakeholder-management, technical writing, presentation, collaboration, and communication skills.
- Familiarity with the telco domain, IT systems, and data-driven use cases, with an interest in emerging AI and data technologies.
Benefits
- Meaningful work shaping enterprise AI initiatives at Singtel.
- Continuous learning and opportunities for career development.
- The posting does not state a work arrangement, contract duration, or compensation details.
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About Singtel
Singtel is a Singapore‑headquartered public telecommunications group founded in 1879 that sells mobile, broadband, and enterprise network services to consumers and businesses across Asia-Pacific. It owns Optus in Australia and operates NCS (regional IT services) and Nxera (data centers), and is expanding into AI infrastructure via its RE:AI GPU‑as‑a‑Service. Its revenue comes from connectivity subscriptions and managed services across networks, cloud, cybersecurity, and digital platforms, with equity stakes in regional operators broadening its reach.