Agentic and Generative AI Engineer

VAT Group; Seberang Perai; On-site; MYR 80,000 - 120,000; Full time

Job summary

A global technology company is seeking an experienced AI Solutions Engineer to design, develop, and enhance AI solutions that drive measurable business value. You'll work on various projects that include automated processes, quality checks, and data management. Ideal candidates will have a background in data engineering and AI solution deployment, alongside strong programming skills in Python or C#. The position requires a proactive approach to continuous learning and collaboration across teams.

Qualifications

• Minimum 3 years of experience as a Data Engineer or in a similar role.
• Hands-on programming expertise in Python and/or C#.
• Practical experience with CI/CD pipelines.

Responsibilities

• Design and implement advanced AI solutions using Agentic and Generative AI technologies.
• Develop multi-agent systems based on the Agent-to-Agent principle.
• Leverage Azure AI Foundry for model development and deployment.

Skills

Data Engineering

AI solution development

Python programming

C# programming

Cloud platforms (Azure, AWS)

Prompt engineering

Data management

CI/CD pipelines

Agile methodology

Communication skills

Education

Bachelor’s degree in Computer Science or related field

Job description

You will design, develop, and continuously enhance Agentic and Generative AI solutions to automate, optimize, and digitize business processes. By transforming innovative ideas into robust, productive applications, the role drives measurable business value through process improvements, cost savings, and the creation of new digital capabilities that align with strategic objectives. Typical use cases include document data extraction and transfer to Master Data Management systems, visual inspection for automated quality checks in manufacturing, chatbots for financial reporting and code generation, as well as solutions for board meeting report preparation and market analysis.

Responsibilities

• Design and implement advanced AI solutions using Agentic AI and Generative AI technologies.
• Architect and optimize Retrieval-Augmented Generation (RAG) pipelines for scalable, context-aware applications.
• Integrate and manage Model Context Protocol (MCP) to enable seamless interaction between AI models and external systems.
• Develop multi-agent systems based on the Agent-to-Agent principle, fostering autonomous collaboration and decision-making.
• Collaborate with cross-functional teams to translate business requirements into robust, scalable AI solutions.
• Ensure robustness, security, and compliance across all AI-driven applications.
• Partner with business units and enterprise architecture teams to analyze requirements and define impactful AI use cases.
• Leverage Azure AI Foundry for model development and deployment.
• Design and maintain interfaces for AI services and applications.
• Build and manage automated pipelines for training, testing, and deployment (CI/CD for AI models), including monitoring for performance and drift.
• Create comprehensive technical documentation and share knowledge with development and business teams.
• Evaluate emerging AI technologies, frameworks, and tools to continuously enhance the AI ecosystem.
• Guarantee traceability, fairness, and compliance of deployed AI models.
• Promote ethical AI practices, ensuring fairness, transparency, and adherence to data privacy regulations.
• Engage with stakeholders to gather requirements, communicate insights, and align AI initiatives with business strategy.
• Stay current with AI research, tools, and best practices through continuous learning and active participation in the AI community.

Required Qualifications

• Minimum 3 years of experience as a Data Engineer or in a similar role focused on data infrastructure, pipelines, or platform engineering.
• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or related field — or equivalent professional experience.
• Proven track record in developing and deploying AI solutions.
• Hands‑on programming expertise in languages such as Python and/or C#, with strong coding and debugging skills.
• Experience with cloud platforms (e.g., Azure, AWS) and their AI services for scalable solution delivery.
• Proficiency in prompt engineering—crafting, evaluating, and refining prompts to optimize generative AI model performance.
• Solid understanding of data management, feature engineering, and data visualization techniques.
• Practical experience with CI/CD pipelines and deploying AI models into production environments.
• Strong communication skills to explain complex technical concepts clearly to both technical and non-technical stakeholders.
• Experience working in interdisciplinary teams and agile environments, fostering collaboration and adaptability.

Competencies

• Analytical thinking: Ability to analyze complex problems and develop data-driven solutions.
• Technical excellence: Deep understanding of modern AI methods, algorithms, and software development.
• Innovation: Openness to new technologies and creative approaches.
• Teamwork: Effective collaboration with diverse stakeholders.
• Communication: Ability to convey complex topics to technical and non-technical audiences.
• Initiative: Proactive identification and implementation of optimization opportunities.
• Quality awareness: High standards for traceability and robustness of developed solutions.
• Learning agility: Ability to quickly adapt to new technologies and domains.
• Business orientation: Ability to link AI solutions to measurable business outcomes.
• Ethical responsibility: Commitment to fairness, transparency, and compliance in AI systems.
• Stakeholder engagement: Strong collaboration and communication skills to align AI projects with business needs.
• Continuous learning: Proactive approach to staying current with AI trends and technologies.

Continuous learning: Proactive approach to staying current with AI trends and technologies.