AI Engineer

RISKDATA CONSULTING PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

RISKDATA CONSULTING PTE. LTD. in Singapore seeks a senior AI/ML engineer to lead development of analytics, machine learning, and AI-driven solutions for business challenges. You will design AI products, build production-ready agents and applications, and shape cloud-based architecture.

You will collaborate across teams, apply Agile methods, and drive end-to-end lifecycle from roadmap to deployment, with emphasis on standardised engineering practices and scalable data solutions.

Qualifications

• Experience in Agentic AI engineering, web app development, or data science.
• Hands-on with AI techniques and practical AI frameworks.
• Familiar with AI tools, frameworks, and open-source libraries.
• Knowledge of database design and cloud services.
• Experience with Agile delivery and cloud platforms.
• Strong problem solving and stakeholder management skills.

Responsibilities

• Lead development of analytics, ML, and AI-driven solutions for business challenges.
• Design, develop, and implement AI products and agent-based applications.
• Build and productionize AI-powered agents and apps.
• Develop software across frontend/backend with cloud data architecture.
• Improve workflows with automation and reusable components.
• Collaborate with teams to ensure quality and timely delivery.

Skills

Agentic AI

Web development

Data science

Agile

Cloud computing

AI frameworks

Testing & QA

DevOps

Containerization

Cross-functional

Education

Bachelor’s degree or higher

Tools

n8n

Dataiku

Databricks

Snowflake

Power Automate

Job description

• Lead the development of advanced analytics, machine learning, and AI-driven solutions to address business challenges and generate actionable insights.
• Design, develop, and implement AI products, including applications leveraging Agentic AI frameworks for practical business use cases.
• Build and maintain agents and applications powered by AI, taking solutions from proof-of-concept to production.
• Design, develop, and implement software solutions across frontend and backend systems, incorporating cloud application and data architecture principles.
• Improve development and workflows through automation, reusable components, tooling, and standardised technical engineering practices.
• Conduct comprehensive functional and performance testing using a range of techniques, agents and tools to ensure high-quality solution delivery.
• Collaborate with technology teams on cloud-based agent and application architecture, design, and implementation.
• Analyse business requirements and recommend technology solutions using Agile delivery methodologies.
• Support the end-to-end product lifecycle, including roadmap planning, development, testing, deployment, and continuous enhancement.
• Define non-functional requirements and assess database solutions in compliance with relevant regulations.
• Work closely with cross-functional stakeholders to ensure successful delivery of products and solutions and identify opportunities to apply AI and automation in the business.

Requirements

• Relevant experience in Agentic AI engineering, web application development, data science, or related disciplines.
• Knowledge of AI techniques, including hands-on experience developing and implementing skills, harnesses, MCPs, Agentic AI frameworks in practical applications.
• Familiarity with AI tools, frameworks, and open-source libraries relevant to the field.
• Knowledge of database design, implementation, and management.
• Familiarity with Agile delivery methodologies and cloud computing platforms and services.
• Strong analytical and problem-solving skills, with the ability to translate complex business problems into effective technology solutions.
• Excellent communication and stakeholder management skills, with the ability to collaborate effectively across multidisciplinary teams and explain technical concepts to diverse audiences.
• Experience with commercial AI, workflow, data and data science platforms such as n8n, Northflank, Copilot in Power Automate, Dataiku, Databricks, Snowflake, etc.; or Whole-of-Government AI tools, such as GovTech Desk, OPUS, Airbase/Airlift, etc would be advantageous.
• Familiarity with containerization and orchestration, as well as automated build, test and deployment pipelines.
• Demonstrated commitment to continuous learning and keeping current with the latest developments in AI, data science, and software engineering.