AI Engineer: Enterprise Automation & Intelligent Workflows

EVOLUTION RECRUITMENT SOLUTIONS PTE. LTD.

Singapore

On-site

SGD 120,000 - 180,000

Full time

14 days+

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Job summary

Evolution Recruitment Solutions Pte. Ltd. is seeking an experienced AI and Machine Learning Engineer to design and deliver intelligent automation solutions that enhance enterprise operations across functions.

The role combines AI engineering, ML, and data analytics to build scalable AI-powered applications that improve decision-making and streamline workflows. You will collaborate with business stakeholders, analytics teams and technical specialists to deploy AI solutions using cloud and

Qualifications

Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence or related discipline.
At least four years of experience in AI engineering, machine learning, data engineering or intelligent automation.
Strong programming skills in Python and SQL.
Hands-on experience with Microsoft Power Platform, including Power Automate, Power Apps, Copilot Studio or related technologies.
Experience building machine learning models including regression, classification, clustering, anomaly detection and time-series forecasting.
Familiarity with Microsoft Azure, including Azure AI services and Azure ML.
Understanding of large language models, retrieval-augmented generation, prompt engineering and AI agent development is desirable.
Experience working with structured enterprise data and semi-structured data such as documents or system logs.
Strong communication skills with ability to explain technical concepts to both technical and non-technical stakeholders.
Experience supporting Finance, HR, Shared Services or other enterprise business functions would be an advantage.

Responsibilities

Design, develop and deploy AI-powered agents to automate business processes and operational workflows.
Integrate AI solutions with enterprise applications and business platforms via APIs and workflow tools.
Build monitoring and observability to measure AI agent performance and usage.
Develop knowledge-aware AI solutions using retrieval-augmented generation and prompt orchestration.
Ensure AI solutions follow security, governance, version control and audit requirements.
Analyse datasets to identify trends and automation opportunities.
Build and evaluate ML models for anomaly detection, forecasting and risk assessment.
Deploy ML models into BI platforms or AI apps using cloud services or Python-based solutions.
Partner with analytics teams to convert model outputs into dashboards and insights.
Monitor performance and optimise AI models through data-driven evaluation.
Translate operational requirements into AI models and automation workflows.
Collaborate with data teams to ensure high-quality, governed data.
Maintain technical documentation for AI models, pipelines, prompts and deployment processes.