Specialist, Automation Scientist

TNG Digital Sdn Bhd; Kuala Lumpur; On-site; MYR 180,000 - 300,000; Full time

Job summary

TNG Digital Sdn Bhd in Kuala Lumpur seeks an experienced Automation Scientist to design and deploy AI-powered automation across enterprise data. You will develop end-to-end AI workflows, integrate LLMs and RAG, and collaborate with data engineers to ensure scalable, secure solutions.

This role requires strong communication with stakeholders, ownership from concept to deployment, and the ability to operate in ambiguous problem spaces.

Qualifications

• Strong foundation in data science, analytics and applied machine learning.
• Experience with LLMs, prompt engineering, and RAG architectures.
• Ability to design end-to-end AI-driven automation solutions in enterprise environments.

Responsibilities

• Design, develop, and deploy end-to-end AI-driven automation solutions using LLMs, RAG pipelines and traditional models.
• Build structured, multi-step workflows combining AI inference, business rules, data retrieval, and HITL controls.
• Ensure production-ready, observable models aligned with enterprise standards for performance and governance.
• Partner with business stakeholders to translate requirements into executable AI workflows and drive high-impact implementations.

Skills

Data science

Applied machine learning

Large Language Models

Prompt engineering

RAG architectures

Workflow orchestration

Data pipelines

Stakeholder management

Communication

Job description

# Specialist, *Automation Scientist*Kuala Lumpur, MalaysiaPermanent#### Duties & Responsibilities* 1. AI & Automation Solution Development* a. Design, develop, and deploy end-to-end AI-driven automation solutions, integrating LLMs, RAG pipelines, and traditional analytics or ML models.* b. Build structured, multi-step workflows that combine AI inference, business rules, data retrieval, and human-in-the-loop (HITL) controls where required.* c. Architect and implement Retrieval-Augmented Generation solutions over structured and unstructured enterprise data sources, ensuring accuracy, relevance, and traceability.* 2. Modelling, Analytics & Engineering* a. Develop and maintain analytical models, machine learning models, and AI components that support automation use cases.* b. Ensure models and AI solutions are production-ready, observable, and aligned with enterprise standards for performance, reliability, and governance.* c. Collaborate with platform and data engineering teams to integrate solutions into the unified AI and data ecosystem.* 3. Stakeholder Engagement & Solutioning* a. Partner closely with business stakeholders to understand processes, pain points, and automation opportunities.* b. Translate ambiguous business requirements into clear technical designs and executable AI workflows.* c. Lead solution discussions, articulate trade-offs, and guide stakeholders toward pragmatic, high-impact implementations.* 4. Governance, Quality & Continuous Improvement* a. Ensure responsible and secure use of AI, including prompt design, data handling, and model behaviour controls.* b. Monitor deployed solutions for quality, drift, and business effectiveness, iterating as requirements evolve.* c. Contribute to internal best practices, reusable components, and standards for AI-driven automation.#### Requirements* Technical* Strong foundation in data science, analytics, and applied machine learning.* Solid understanding of Large Language Models (LLMs), including prompt engineering, evaluation, and integration patterns.* Hands-on experience designing and implementing Retrieval-Augmented Generation (RAG) architectures.* Experience building structured workflows that orchestrate AI models, data pipelines, and business logic.* Ability to work with both structured and unstructured data sources in enterprise environments.* Professional & Soft Skills* Proven ability to take ownership of solutions from concept to deployment.* Strong communication skills, with the ability to explain technical concepts to non-technical stakeholders.* Demonstrated experience in stakeholder management, alignment, and collaborative solutioning.* Highly driven, proactive, and comfortable operating in ambiguous problem spaces.* Experience* Several years of experience in data science, applied AI, automation, or advanced analytics roles.* Experience delivering internal automation or enterprise AI solutions is strongly preferred.