We are seeking a highly skilled AI Engineer to join our team. In this role, you will design, build, and deploy scalable AI and Machine Learning solutions. You will work across Data Engineering, DevOps, and Machine Learning disciplines to deliver robust Generative AI and traditional ML solutions.

You will apply modern frameworks and cloud services to solve complex business challenges, ensuring AI systems are reliable, efficient, and secure.

Key responsibilities

• Design and implement end-to-end AI/ML pipelines from data ingestion to deployment and monitoring
  
• Build and optimise Generative AI applications using RAG (Retrieval-Augmented Generation) architectures and LLM frameworks
  
• Develop and maintain scalable data processing workflows using modern big data tools
  
• Implement MLOps best practices for model lifecycle management, versioning, and automated deployment
  
• Collaborate with data scientists and stakeholders to translate business requirements into technical solutions
  
• Ensure data quality, governance, and security across all AI and data platforms
  

Requirements

Requirements

• Minimum of 5 years professional experience
  
• At least 2 years in AI/ML
  
• At least 1 year in Generative AI is highly desirable
  

Skills and Experience

Core skills, tools, and frameworks

• Expert-level Python, strong OOP, design patterns, and asynchronous programming
  

• Experience with LangChain, Langflow, AutoGen, agent development, and LLM orchestration
  

• Strong understanding of RAG, vector search (Pinecone, Chroma, Milvus), and advanced prompt engineering
  

• MLflow, feature stores, and model serving (TFServing, TorchServe, KServe)
  

• PySpark, Spark SQL, Delta Lake
  

• Git workflows, GitHub Actions, Azure DevOps
  

• Apache Airflow, Databricks Workflows, Delta Live Tables
  

• Medallion Architecture, ETL/ELT, data modelling
  

• Unity Catalog, lineage, access control, and security
  

• Kafka, AWS Kinesis, Spark Structured Streaming
  

• Great Expectations, Deequ
  

• PowerBI, Tableau, Databricks SQL Dashboards
  

• Amazon S3
  
• AWS IAM
  
• VPC and networking concepts
  
• Amazon Bedrock
  
• Amazon SageMaker
  
• Amazon Kinesis
  

Azure skills

• Azure Data Lake Storage Gen2
  
• Azure OpenAI Service
  
• Azure AI Search
  
• ARM templates / Bicep
  
• Azure monitoring
  
• VNETs, Private Endpoints, Managed Identities, Key Vault
  

Databricks skills

• Mosaic AI
  
• MLflow
  
• Unity Catalog
  
• Databricks Jobs, Workflows, DLT
  
• Spark SQL and PySpark optimisation
  
• Databricks CLI and REST API automation
  

Certifications (nice to have)

Core & General

• NVIDIA Certified Associate: AI in the Data Center or similar
  
• DeepLearning.AI Generative AI and LLM specialisations
  

AWS:

• AWS Certified Machine Learning – Specialty
  
• AWS Certified Solutions Architect – Associate
  

Azure:

• Microsoft Certified: Azure AI Engineer Associate (AI-102)
  
• Microsoft Certified: Azure Data Scientist Associate (DP-100)
  

Databricks:

• Databricks Certified Machine Learning Professional
  
• Databricks Certified Generative AI Engineer Associate
  
• Databricks Certified Data Engineer Professional