AI Engineer

Responsibilities

Responsible for designing, developing, and maintaining scalable web applications related to machine learning and artificial intelligence using modern cloud-native architectures. This role involves working across the entire technology stack, from micro-frontend user interfaces to backend microservices, leveraging Azure cloud services and event-driven architectures.

Technical Skillset

General Skillset

-        Cloud Platforms (e.g. Azure)

-        Microservices architecture and event-driven patterns (e.g. Kafka)

-        Containerisation and orchestration tools (e.g. Docker, Kubernetes, Kubectl command, Helm chart, FluxCd)

-        Database technologies (e.g. SQL, MongoDB, Postgres)

-        Unit Testing (xUnit, Jasmine/Karma)

Backend and Frontend Technologies

-        Node.js, Python 

-        JavaScript/TypeScript, HTML5, CSS3, Vue

-        API development tools (e.g. Swagger and Postman)

-        Wireframing (e.g. Figma)

Large Language Model Integration 

-     LLM APIs (e.g. Azure OpenAI) 

-     Retrieval-augmented generation (RAG) and embedding systems 

-     Prompt engineering, prompt chaining, and context management 

-     Token management, cost optimisation, performance tuning and rate limiting strategies for scalable deployment

-     Knowledge of data privacy, responsible AI practices, and compliance with GenAI governance

Knowledge Management and Retrieval 

-     Vector databases 

-     Knowledge graph construction and graph databases (Neo4j) 

-     Document processing, chunking strategies, and semantic search 

-     Hybrid search approaches combining semantic and keyword search 

Agentic Workflow Implementation 

-     Agent frameworks (e.g. LangChain) 

-     Multi-agent orchestration and agent communication protocols 

-     Agent workflow engines and task delegation systems 

Other Skillset

-        Experience working with Agile teams with strong collaboration skills

-        Experience with software best practices and principles ensuring clean, maintainable and efficient codes.

-        Knowledge/experience of frontend security (e.g. CSP, CORS, XSS prevention). 

-        Knowledge/experience with backend security (e.g. OAuth, JWT, API rate limiting, encryption). 

-        Knowledge/experience with cloud security (e.g. IAM, Secrets Management, OWASP Top 10). 

-        Familiarity with IM8 guidelines, standards and requirements 

-        Stakeholders engagement/management and requirements analysis skills 

-        Good presentation and interpersonal skills 

Experience Requirements

-     Minimum 2 years experience in developing and/or maintaining systems with AI/ML capabilities.

-     Minimum 3 years experience in designing, developing and/or maintaining systems with AI/ML capabilities of at least 500 man-days.

-     Played the role of a technical lead to a team of developers.

-     Minimum 5 years experience in designing, developing and/or maintaining systems with AI/ML capabilities of at least 1,000 man-days.

-     Led a team of at least 5 members to deliver a project.

Qualification1 Requirements

-        Degree or Diploma in Computer Science, Computer Engineering, Information Technology or related disciplines