AI ML Engineer

• Education: Degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Information Systems or a related technical discipline. 
• Experience: 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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Skills

API Development, AWS, LangGraph, Amazon Redshift, Responsible AI, Artificial Intelligence, LLMOps, AI Evaluation, LLMs, Version Control Systems, CI/CD, RAGAS, Cloud Services, Data Science, Business Requirements Mapping, Workflow Applications, CrewAI, Solution Deployment, Agentic AI, Redshift