AI Engineer

U3 PROJECTS PTE. LTD.; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

U3 PROJECTS PTE. LTD. seeks a developer to build and operationalize AI, automation and data solutions that enhance cybersecurity analytics, decision-making and incident response.

You will collaborate with cybersecurity specialists and technology teams to turn business needs into secure, scalable solutions. The role focuses on delivering AI-enabled applications, integrating models with APIs and cloud services, and implementing robust testing, security and handover practices to ensure reliable

Qualifications

• Strong software development experience, especially Python and modern application frameworks.
• Hands-on experience building LLM applications, agents, retrieval solutions or multi-step orchestration workflows.
• Experience with APIs, data integration, cloud development (AWS preferred).
• Knowledge of DevOps/CI/CD practices, including automated testing, version control, secrets management, containerization, deployment pipelines and production diagnostics.
• Strong analytical, problem-solving and stakeholder collaboration skills.
• Positive and collaborative mindset with good written and verbal communication.
• Agile, fast learner and adaptable.

Responsibilities

• Develop AI-enabled applications, agents, workflows and automation for cybersecurity use cases.
• Translate operational challenges into testable use cases, prototypes and production solutions.
• Integrate AI models with enterprise systems, APIs, data pipelines and cloud services.
• Establish testing, evaluation, documentation, monitoring and operational handover practices.
• Apply appropriate security, access control, human oversight and failure-handling safeguards.

Skills

Python

LLM applications

APIs & data integration

DevOps & CI/CD

AWS cloud development

Analytical skills

Stakeholder collaboration

Communication skills

Education

Bachelor's degree in CS/related field

Tools

Databricks

Git

OCSF

Job description

Summary:

· The successful candidate is expected to build and operationalize AI, automation and data solutions that improve cybersecurity analytics, decision-making and operational response.

· The person will work with cybersecurity specialists and technology teams to turn business needs into secure, reliable and scalable solutions.

Key Responsibilities:

· Develop AI-enabled applications, agents, workflows and automation for cybersecurity use cases.

· Translate operational challenges into testable use cases, prototypes and production solutions.

· Integrate AI models with enterprise systems, APIs, data pipelines and cloud services.

· Establish testing, evaluation, documentation, monitoring and operational handover practices.

· Apply appropriate security, access control, human oversight and failure-handling safeguards.

Skills:

· Strong software development experience, particularly in Python and modern application frameworks.

· Hands-on experience in building Large Language Model (LLM) applications, agents, retrieval solutions or multi-step orchestration workflows.

· Experience with APIs, data integration, cloud development (preferably AWS).

· Working knowledge of DevOps or CI/CD practices, including automated testing, version control, secrets management, containerization, deployment pipelines, and production diagnostics.

· Strong analytical, problem-solving and stakeholder collaboration skills.

· Possess positive and collaborative mindset.

· Good written and verbal communication skills.

· Agile, fast learner and able to adapt to changes.

Good to have:

Experience in one or more of the following areas is advantageous. Candidates are not expected to cover all three groups.

1. Cybersecurity

• Security operations (SecOps), such as vulnerability management, threat intelligence, incident response or detection engineering.
• Red and blue teaming, including testing AI systems for misuse and failure modes.
• Enterprise identity, network, proxy, governance or data access controls.

2. Data and platforms

• Data engineering or data lake house platforms, such as Databricks.
• Open Cybersecurity Schema Framework (OCSF), security data normalization or cross-source event correlation.
• Full-stack product development and UI/UX.

3. AI evaluation and serving

• LLM evaluation, benchmarking, model selection or finetuning.
• Model serving, inference optimization, GPU infrastructure or local model deployment.