AI Engineer

Core AI/ML Skills

5+ years of software engineering experience with at least 2+ years focused on AI/ML and

Generative AI solutions.

Hands-on experience with Amazon Bedrock and Bedrock Knowledge Bases.

Strong understanding of Retrieval-Augmented Generation (RAG) architectures.

Experience building document ingestion pipelines and vector search solutions.

Expertise in prompt engineering, context optimization, and LLM evaluation.

Experience developing AI agents, skills, and orchestration workflows.

Programming & Development

Proficiency in Python and modern software development practices.

Experience developing REST APIs and microservices.

Strong understanding of software architecture, integration patterns, and distributed systems.

Familiarity with version control, testing, and CI/CD practices.

AWS & Cloud

Experience deploying applications on AWS cloud services.

Hands-on experience with Amazon ECS and containerized deployments.

Understanding of IAM, security best practices, and cloud-native architectures.

Experience with monitoring, logging, and operational support in cloud environments.

Enterprise Integration

Experience integrating Microsoft Graph APIs and Microsoft Exchange services.

Strong knowledge of OAuth 2.0 authentication and authorization frameworks.

Experience designing workflow automation and human approval processes.

Good to Have

Backend / Application Development

Experience building API aggregation and response-shaping layers (BFF architecture).

Knowledge of federated Active Directory authentication and OAuth token exchange.

Experience implementing agent, skill, and knowledge base access controls.

Familiarity with IAM policies, resource-level permissions, and sharing workflows.

2DevOps / Cloud Engineering

Experience implementing AI and LLM observability using CloudWatch and related monitoring

tools.

Knowledge of Bedrock model invocation metrics and performance monitoring.

Experience with cloud cost tracking, resource tagging, and billing allocation.

Familiarity with audit logging, compliance reporting, and governance frameworks.

Experience with Infrastructure as Code (CloudFormation, AWS CDK, Terraform).

Knowledge of CI/CD pipelines, multi-environment deployments, runbooks, and scaling policies.

Preferred Qualifications

Experience building enterprise AI assistants, copilots, or agentic AI platforms.

Knowledge of vector databases, embeddings, and semantic search technologies.

Experience working in regulated or enterprise environments with strong governance

requirements.

AWS certifications such as AWS Certified Machine Learning Engineer, AWS Certified Solutions

Architect, or equivalent.

Experience with AgentCore or similar agent orchestration platforms.

Education

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning,

Software Engineering, or a related field.

Equivalent practical experience will also be considered.

Pay: $5,000.00 - $11,599.69 per month

Experience:

• overall : 4 years (Preferred)

License/Certification:

• AWS Certification (Required)

Location:

• Singapore (Required)

Work Location: In person