C
CelcomDigi
AI SOLUTION ARCHITECT
Skills
Google Cloud PlatformData ScienceDatabricksCybersecurityData AnalysisMachine LearningAIAWSNLP / Natural Language ProcessingSAP SuccessFactorsComplianceAzure
1 month ago
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Important information
Location:
Petaling Jaya, Selangor, Malaysia
Work mode:
Onsite
Published on:
22 September 2026
What they need
Responsibilities
- Execute end-to-end AI solution architecture and technical solutioning for enterprise opportunities.
- Translate customer business requirements into secure, scalable, responsible and commercially viable AI solutions.
- Execute customer discovery, AI strategy workshops, demonstrations, architecture reviews, use-case assessments and proof-of-concepts.
- Assist in developing AI solution architectures, HLD/LLD, data-flow designs, sizing, BoM, costing, implementation roadmaps and proposals for RFI/RFP/tenders.
- Design solutions across generative AI, LLMs, machine learning, computer vision, NLP, intelligent automation, conversational AI, agents and predictive analytics.
- Architect enterprise AI platforms across public, private and hybrid cloud, including data platforms, training, fine-tuning, inference, RAG, vector databases, APIs and MLOps/LLMOps.
- Establish secure and responsible AI architectures covering privacy, IAM, governance, explainability, bias, content safety, compliance, auditability and human oversight.
- Work closely with Sales, Product, Engineering, Delivery, Managed Services, Cybersecurity, Legal, Finance and Bid Management to ensure technically sound, deliverable and commercially competitive solutions with healthy margins.
- Evaluate AI technologies; build reusable architectures and best practices; engage technology partners; lead commercial and delivery transition risks; define success measures and production operating processes.
Requirements
- More than 5 years in business analysis, solution architecture, data, software engineering or enterprise AI and cloud workflow solutioning, with strong business acumen and interpersonal skills.
- Degree in Computer Science, IT, Data Science, AI, Engineering or related discipline, with relevant Azure AI, AWS ML, Google Cloud AI, NVIDIA, Databricks or equivalent certification.
- Analytical and strategic thinking with strong business acumen
- Strong AI, machine learning, generative AI, data platform and cloud architecture knowledge
- Strong stakeholder management, problem-solving and leadership
- Good communication, presentation and interpersonal skills
- Strong AI security, governance, privacy, risk and responsible-AI knowledge
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