We are seeking a highly skilled AI Engineer to join our 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
Programming mastery:
- Expert-level Python strong OOP design patterns and asynchronous programming
AI & LLM frameworks:
- Experience with LangChain Langflow AutoGen agent development and LLM orchestration
GenAI architecture:
- Strong understanding of RAG vector search (Pinecone Chroma Milvus) and advanced prompt engineering
ML engineering & MLOps:
- MLflow feature stores and model serving (TFServing TorchServe KServe)
Big Data processing:
- PySpark Spark SQL Delta Lake
Version control & CI/CD:
- Git workflows GitHub Actions Azure DevOps
Orchestration:
- Apache Airflow Databricks Workflows Delta Live Tables
Data architecture:
- Medallion Architecture ETL/ELT data modelling
Data governance:
- Unity Catalog lineage access control and security
Streaming:
- Kafka AWS Kinesis Spark Structured Streaming
Data quality:
BI & visualisation:
- PowerBI Tableau Databricks SQL Dashboards
AWS skills
- 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
- 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
Required Skills:
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 Programming mastery: Expert-level Python strong OOP design patterns and asynchronous programming AI & LLM frameworks: Experience with LangChain Langflow AutoGen agent development and LLM orchestration GenAI architecture: Strong understanding of RAG vector search (Pinecone Chroma Milvus) and advanced prompt engineering ML engineering & MLOps: MLflow feature stores and model serving (TFServing TorchServe KServe) Big Data processing: PySpark Spark SQL Delta Lake Version control & CI/CD: Git workflows GitHub Actions Azure DevOps Orchestration: Apache Airflow Databricks Workflows Delta Live Tables Data architecture: Medallion Architecture ETL/ELT data modelling Data governance: Unity Catalog lineage access control and security Streaming: Kafka AWS Kinesis Spark Structured Streaming Data quality: Great Expectations Deequ BI & visualisation: PowerBI Tableau Databricks SQL Dashboards AWS skills 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 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
We are seeking a highly skilled AI Engineer to join our 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 mo...
We are seeking a highly skilled AI Engineer to join our 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
Programming mastery:
- Expert-level Python strong OOP design patterns and asynchronous programming
AI & LLM frameworks:
- Experience with LangChain Langflow AutoGen agent development and LLM orchestration
GenAI architecture:
- Strong understanding of RAG vector search (Pinecone Chroma Milvus) and advanced prompt engineering
ML engineering & MLOps:
- MLflow feature stores and model serving (TFServing TorchServe KServe)
Big Data processing:
- PySpark Spark SQL Delta Lake
Version control & CI/CD:
- Git workflows GitHub Actions Azure DevOps
Orchestration:
- Apache Airflow Databricks Workflows Delta Live Tables
Data architecture:
- Medallion Architecture ETL/ELT data modelling
Data governance:
- Unity Catalog lineage access control and security
Streaming:
- Kafka AWS Kinesis Spark Structured Streaming
Data quality:
BI & visualisation:
- PowerBI Tableau Databricks SQL Dashboards
AWS skills
- 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
- 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
Required Skills:
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 Programming mastery: Expert-level Python strong OOP design patterns and asynchronous programming AI & LLM frameworks: Experience with LangChain Langflow AutoGen agent development and LLM orchestration GenAI architecture: Strong understanding of RAG vector search (Pinecone Chroma Milvus) and advanced prompt engineering ML engineering & MLOps: MLflow feature stores and model serving (TFServing TorchServe KServe) Big Data processing: PySpark Spark SQL Delta Lake Version control & CI/CD: Git workflows GitHub Actions Azure DevOps Orchestration: Apache Airflow Databricks Workflows Delta Live Tables Data architecture: Medallion Architecture ETL/ELT data modelling Data governance: Unity Catalog lineage access control and security Streaming: Kafka AWS Kinesis Spark Structured Streaming Data quality: Great Expectations Deequ BI & visualisation: PowerBI Tableau Databricks SQL Dashboards AWS skills 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 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
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