Company Overview
NCS is a leading AI Tech Services company. With a 15,000-strong team across the Asia Pacific, NCS scales its platforms and capabilities to provide clients with greater agility and AI expertise across a range of industries. Embracing a strong ecosystem of global partners, NCS transforms technology services delivery combining AI with digital resilience to drive real business impact. NCS is a subsidiary of the Singtel Group.
About The Role
We are seeking an exceptional AI Architect to lead the design, development, and delivery of enterprise AI solutions across traditional machine learning, generative AI, and agentic AI systems. This role demands a unique combination of deep technical expertise and strong leadership capabilities—you must be equally comfortable architecting complex AI platforms, rolling up your sleeves to code hands-on implementations, and engaging confidently with senior stakeholders to drive business outcomes. The ideal candidate brings proven experience deploying ML models in commercial production environments, a sophisticated understanding of GenAI design patterns and evaluation frameworks, and the ability to translate cutting-edge AI developments into pragmatic, implementable solutions. You will drive technical teams to deliver on time while maintaining the learning mindset necessary to stay at the forefront of this rapidly evolving field, all while building strong client relationships through excellent communication and confident technical leadership.
Key Responsibilities
Technical Leadership & Architecture
- Design and architect end-to-end AI solutions spanning traditional ML, generative AI, and Agentic AI systems
- Evaluate and select appropriate design patterns for GenAI implementations, clearly articulating tradeoffs between approaches (RAG vs fine-tuning, prompt engineering strategies, agent orchestration patterns, etc.)
- Define and implement comprehensive evaluation frameworks for GenAI systems, including quality metrics, performance benchmarks, and responsible AI considerations
- Stay current with emerging AI/ML developments and assess their practical applicability to client environments
Client Engagement & Stakeholder Management
- Serve as trusted technical advisor to clients, translating complex AI concepts into business value
- Lead solution workshops and technical pre-sales presentations with C-level executives and technical teams
- Build and maintain strong client relationships through confident communication and delivery excellence
- Bridge the gap between cutting-edge AI capabilities and pragmatic, implementable solutions
Team Leadership & Delivery
- Drive technical teams to deliver high-quality AI solutions on time and within scope
- Provide hands-on technical guidance and code reviews, leading by example
- Manage delivery timelines and proactively identify and mitigate risks
- Mentor team members on AI best practices, design patterns, and implementation approaches Hands-On Development
- Contribute directly to architecture and code implementation when needed
- Build proof-of-concepts and prototypes to validate technical approaches
- Debug complex technical issues across the AI stack
- Ensure code quality, scalability, and maintainability standards
Minimum Qualifications
Required Qualifications:
- 8+ years of experience in AI/ML engineering and architecture
- Proven track record of implementing ML models in commercial production environments
- Deep expertise in traditional machine learning (supervised/unsupervised learning, feature engineering, model optimization)
- Significant experience with Generative AI technologies (LLMs, prompt engineering, RAG, fine-tuning, vector databases)
- Hands-on experience building agentic AI systems and multi-agent architectures
- Strong programming skills in Python and relevant ML/AI frameworks (SKlearn, XGBoost, PyTorch, TensorFlow, LangChain, LlamaIndex, etc.)
- Demonstrated ability to design and implement GenAI evaluation
- Excellent communication skills with ability to present complex technical topics clearly to both technical and non-technical audiences
- Strong project management capabilities with history of delivering complex projects on schedule
Preferred Qualifications
- Experience with enterprise AI platform development and MLOps practices Knowledge of AI governance frameworks and responsible AI practices
- Familiarity with cloud platforms (AWS, Azure, GCP) and their AI/ML services Experience with real-time AI systems and low-latency architectures
- Background in telecommunications, financial services, or other regulated industries Advanced degree in Computer Science, AI/ML, or related technical field
