BackSpecialist, Automation Scientist
NEW
Kuala Lumpur, Malaysia
Permanent
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.
