About the position
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
RequirementsRequirements
- 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
- 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
Desired Skills:
- Programming mastery
- AI & LLM frameworks
- GenAI architecture
- ML engineering & MLOps
- Big Data processing
- Version control & CI/CD
Desired Qualification Level:
About The Employer:
