ML/AI Engineer

Education: Degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Information Systems or a related technical discipline.
Experience: 3–5 years of hands-on experience building and deploying ML/AI applications. This must include at least one LLM-enabled system delivered beyond prototype into operational use.

Technical & Professional Competencies

Strong Python software engineering capability, including API development, testing, version control and modular system design.
Hands-on experience building and deploying ML/AI applications, including at least one LLM-enabled or agentic AI solution beyond proof-of-concept stage.
Experience with LLM applications, retrieval, tool use, workflow orchestration or multi-agent frameworks such as LangGraph, CrewAI or equivalent.
Experience integrating AI/ML solutions with enterprise data platforms, databases, APIs or cloud services.
Ability to design and implement systematic evaluation frameworks for AI systems, including testing, benchmarking, observability and reproducibility.
Working knowledge of AI governance, security and Responsible AI practices, including human-in-the-loop controls, access management, auditability and safeguards against misuse.
Strong problem-solving and analytical skills, with the ability to translate business requirements into scalable AI-enabled solutions. Preferred (Advantageous)
Experience with AWS services such as Bedrock, Redshift, Glue, S3, Lambda or related cloud-native services.
Experience with PySpark, Databricks or large-scale data processing and feature engineering pipelines.
Experience with CI/CD, containerisation, MLOps or model deployment tooling (e.g. Docker, MLflow, GitHub Actions, Jenkins).
Experience implementing monitoring, observability and operational support processes for ML/AI applications.
Experience delivering fraud detection, risk, compliance, investigation or decision support solutions.

Experience with knowledge retrieval, RAG, graph-based workflows, prompt management, model evaluation tooling or AI observability platforms.

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