AI Engineer

Role Overview

Shin Khai Construction Pte Ltd is looking for a highly driven, energetic, and adaptable AI Engineer who is genuinely passionate about Artificial Intelligence (AI) and enjoys exploring emerging technologies. The successful candidate will lead the development and deployment of AI agents across the company and its business operations.

These agents will function as our virtual staff, supporting departments and carrying out defined operational and administrative responsibilities. The AI Engineer will act as the manager of this virtual workforce by designing suitable agents, assigning their functions, evaluating their performance, and fine-tuning, rebuilding, or replacing agents that do not meet operational requirements.

This is a hands-on and business-facing position. The person must be able to turn new AI capabilities into secure, user-friendly, and maintainable solutions that support the organisation's long-term strategy and deliver measurable value.

Key Responsibilities

1 AI Research and Organisational Adoption

· Keep abreast of emerging AI models, platforms, agent frameworks, automation tools, and industry trends.

· Proactively explore and test new AI capabilities and assess their relevance to the organisation.

· Identify opportunities across construction operations, HR, safety, quality, compliance, ESG, procurement, contracts, finance, and administration.

· Convert suitable ideas into proofs of concept, obtain stakeholder feedback, and deploy practical business solutions.

· Promote responsible AI adoption and digital transformation across the organisation.

2 Development of AI Agents and Virtual Staff

· Design, develop, configure, and deploy multiple AI agents to serve as virtual staff for different departments and business functions.

· Define every agent's role, responsibilities, knowledge sources, workflows, access permissions, limitations, and escalation procedures.

· Equip agents to answer inquiries, retrieve information, prepare documents, monitor records, issue reminders, analyze data, and produce reports.

· Integrate agents with approved company systems, documents, databases, communication channels, and third-party applications.

· Ensure agents work effectively with human employees and escalate matters requiring human judgment, verification, or approval.

3 AI Workforce Management

· Maintain an inventory of deployed AI agents, including their purpose, assigned department, system access, and responsible human owner.

· Establish measurable performance standards for accuracy, reliability, response quality, usability, speed, security, and cost-effectiveness.

· Review agent outputs, user complaints, errors, and feedback and implement timely improvements.

· Fine-tune, retrain, reconfigure, or redesign agents that do not meet the required standards.

· Retire and replace ineffective agents and develop new agents where improvement is not technically or commercially practical.

· Ensure each agent continues to provide measurable operational value over its lifecycle.

4 Long-Term and Strategic Agent Development

· Develop agents as reliable, scalable, and maintainable long-term business solutions, not only short-term demonstrations.

· Design agents around the company's long-term strategy, business growth, and changing operational requirements.

· Train and configure agents using approved company knowledge, procedures, workflows, and operational requirements.

· Ensure agents can be updated when policies, regulations, responsibilities, or business processes change.

· Create intuitive and user-friendly experiences for employees with different levels of technical knowledge.

· Maintain clear documentation and a continuous improvement plan for every production agent.

5 Internal Company AI Assistant

· Develop and maintain a secure internal AI assistant that retrieves information from approved company sources.

· Build capabilities covering employee policies, HR procedures, project documents, safety requirements, quality standards, compliance procedures, ESG initiatives, and company SOPs.

· Ground responses in authorized documents and provide references to relevant sources where practicable.

· Apply access permissions according to the user's role, department, and authority.

6 AI Automation and System Integration

· Develop AI-powered workflows that reduce repetitive and manual work.

· Connect approved AI applications with databases, cloud storage, spreadsheets, email, the WhatsApp Business Platform, and other company systems.

· Build and maintain the required APIs, dashboards, databases, and backend services.

· Automate appropriate reminders, approvals, follow-ups, document preparation, data extraction, and management reporting.

· Coordinate with internal users, vendors, and technology partners to implement integrations.

7 Testing and Continuous Improvement

· Test every AI agent before deployment using actual or representative company scenarios.

· Establish evaluation methods for accuracy, relevance, consistency, security, usability, and operational effectiveness.

· Monitor agents after deployment and identify errors, hallucinations, outdated information, and workflow failures.

· Continuously improve prompts, instructions, knowledge sources, workflows, tools, and underlying models.

· Maintain version records so changes can be evaluated, compared, and reversed when necessary.

8 AI Governance, Security, and Data Protection

· Ensure all AI solutions comply with company policies, PDPA requirements, confidentiality obligations, and cybersecurity standards.

· Implement appropriate access controls, approval limits, activity logs, and data-retention requirements.

· Protect employee, worker, customer, tender, contractual, and project information from unauthorized access or disclosure.

· Require human review for important employment, disciplinary, financial, contractual, safety, and compliance decisions.

· Assess third-party AI platforms before company information is uploaded or processed.

9 Deployment and Technical Maintenance

· Deploy approved AI solutions for practical day-to-day use and support them throughout their operational lifecycle.

· Monitor availability, accuracy, response time, usage, errors, and operating costs.

· Troubleshoot technical problems and carry out timely corrective action.

· Maintain technical documentation, source-code control, backups, and change records.

· Select suitable AI models and platforms based on performance, security, scalability, and cost.

10 Stakeholder Communication and User Adoption

· Communicate confidently and professionally with management, employees, department heads, project teams, clients, vendors, and technology partners.

· Conduct requirement-gathering discussions to understand operational problems, expectations, and workflows.

· Translate technical AI concepts into clear and practical language for non-technical users.

· Present AI proposals, demonstrations, progress updates, and performance results to management and stakeholders.

· Coordinate user acceptance testing, training, implementation support, and feedback collection.

· Develop user guides, standard instructions, and training materials for approved AI tools.

11 Performance Reporting

· Maintain an AI project roadmap, implementation schedule, and issue tracker.

· Report progress, adoption, risks, costs, and results to management.

· Measure outcomes such as time saved, reduction in manual work, response time, accuracy, user adoption, and cost savings.

· Ensure every initiative has a defined objective, an accountable owner, and a measurable business outcome.

Candidate Requirements

· Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, or a related field, or equivalent practical experience.

· Demonstrated hands-on experience developing and deploying AI agents, generative AI applications, or AI-powered automation solutions.

· Strong programming ability in Python and experience with APIs, databases, and backend application development.

· Practical knowledge of large language models, retrieval-augmented generation, prompt and context engineering, embeddings, vector search, agent orchestration, and AI evaluation.

· Experience integrating AI solutions with business systems, cloud platforms, or communication tools.

· Understanding of production deployment, monitoring, version control, security, and data-protection practices.

· Strong written and verbal communication, stakeholder-management, and presentation skills.

· Confident, approachable, and outgoing, with the ability to initiate discussions and work effectively with people at different organizational levels.

· Highly driven, energetic, resourceful, and comfortable working in a fast-moving and evolving technology environment.

· Able to work independently, take end-to-end ownership, and collaborate across departments.

· Committed to continuous learning and willing to rebuild or replace solutions when they do not meet the required standard.

Preferred Experience

· Experience with agent frameworks or orchestration tools such as LangGraph, LangChain, LlamaIndex, Semantic Kernel, or equivalent technologies.

· Experience with OpenAI, Azure OpenAI, Anthropic, Google Gemini, open-source models, or comparable AI platforms.

· Experience with SQL, vector databases, Docker, CI/CD, cloud services, and AI observability tools.

· Experience delivering AI solutions for internal operations, enterprise knowledge management, construction, HR, compliance, or workflow automation.

· A portfolio of deployed AI applications or agents with evidence of measurable user or business outcomes.

Interview Demonstration and Assessment

Shortlisted candidates will be required to present and demonstrate one or more AI agents that they personally developed or in which they made a substantial technical contribution. The interview panel will test the demonstrated agent to assess its functionality, accuracy, reliability, usability, response quality, and ability to handle unexpected or challenging scenarios.

Candidates Should Be Prepared to Explain

· The agent's purpose, intended users, and the business problem addressed.

· Their personal role and technical contribution.

· The models, technologies, tools, knowledge sources, and integrations used.

· How the agent was trained, configured, grounded, evaluated, and improved.

· How security, privacy, operating costs, maintenance, and known limitations were addressed.

· How the agent would be scaled or maintained for long-term use.

Confidentiality requirement Candidates must not disclose confidential information, personal data, proprietary source code, or intellectual property belonging to any current or former employer, client, or third party. A personal project, independently developed demonstration agent, or a suitably anonymised portfolio project may be presented.

Application Information

Applicants should submit a resume together with a portfolio or a brief description of the AI agents and AI applications they have developed. The submission should clearly state the candidate's personal contribution, technologies used, deployment status, and measurable results where available.

Compensation

Monthly base salary: S$6,500 to S$9,500. The final offer will depend on relevant experience, technical depth, communication ability, portfolio quality, and performance during the interview assessment.