AI Engineer

Reverside is an established IT services provider delivering high-quality Software Development IT Resourcing Digital Transformation and Systems Support solutions. We are always looking for skilled professionals to join our growing team and contribute to innovative technology projects across various industries. We are seeking an experienced AI Engineer to design build deploy and maintain enterprise AI and machine-learning solutions.

The role focuses on AI Engineering MLOps LLMOps Databricks cloud platforms and scalable AI architectures covering the full AI product lifecycle from data preparation and model development through to deployment monitoring governance and optimisation.

Key Responsibilities:

• Design and develop scalable AI/ML and LLM solutions.
  
• Build MLOps and LLMOps pipelines using Databricks MLflow Delta Lake and Spark.
  
• Develop and deploy machine learning models and AI applications in production environments.
  
• Build RAG LLM agentic and multi-modal AI solutions.
  
• Develop feature engineering data pipelines model-serving and inference solutions.
  
• Implement CI/CD monitoring governance security and responsible AI practices.
  
• Develop prompts agents tools chains and AI workflows with appropriate guardrails.
  
• Build and optimise vector search and retrieval solutions.
  
• Monitor model performance costs quality and scalability.
  
• Collaborate with Data Engineering Data Science business and clinical stakeholders.
  
• Provide technical leadership and mentoring to AI and data teams.
  

• 710 years AI / Machine Learning Engineering
  
• Python & SQL
  
• Databricks & MLflow
  
• MLOps & LLMOps
  
• Apache Spark & Delta Lake
  
• Cloud & Distributed Data Platforms
  
• Machine Learning & Feature Engineering
  
• RAG & LLM Applications
  
• LangChain / AI Agents
  
• Prompt Engineering
  
• Vector Search & Embeddings
  
• Model Serving & Deployment
  
• AI/ML Monitoring & Governance
  
• Big Data & Data Pipelines
  

Advantageous Skills:

• Mosaic AI
  
• Unity Catalog
  
• AWS / Azure Kafka / Hadoop
  
• Healthcare / Clinical Data
  
• Responsible AI & Model Governance
  
• Power BI / Tableau / Kibana
  

Qualifications:

• Honours Masters or PhD in Data Science Statistics Computer Science Engineering Mathematics or related field.
  
• Relevant certifications in Python AWS Microsoft Machine Learning Databricks Big Data or Cloud technologies.
  

Core Competencies:

• Strong analytical and problem-solving skills
  
• AI solution architecture and engineering
  
• Strong communication and stakeholder engagement
  
• Business and technical problem-solving
  
• Ability to work in Agile environments
  
• Technical leadership and mentoring
  
• Strong understanding of AI governance security and responsible AI