Artificial Intelligence Engineer

REMOTE OPPORTUNITY FOR SOUTH AFRICAN AI ENGINEERS.6-12 MONTH ENGAGEMENTThe RoleWe are looking for a Senior Applied AI Engineer to help design, build, and deliver production-ready AI solutions for enterprise clients.This role is suited to someone with strong hands-on experience in AI, machine learning, generative AI, data engineering, and software delivery. The focus is on building practical AI solutions that are scalable, secure, measurable, and ready for real business use.You will work on solutions involving machine learning, LLMs, retrieval-augmented generation, agentic workflows, automation, forecasting, classification, optimisation, anomaly detection, and enterprise data platforms.Key ResponsibilitiesDesign and build applied AI and machine learning solutions for client projects.Develop LLM-based applications, RAG solutions, AI agents, and workflow automation components.Build and maintain data pipelines, feature pipelines, model training workflows, and inference services.Support the productionisation of AI and ML systems using MLOps and LLMOps practices.Implement monitoring, evaluation, testing, and observability for AI systems.Integrate AI solutions with APIs, cloud services, data platforms, and enterprise applications.Work with data scientists, data engineers, software engineers, architects, and delivery teams.Support technical discovery, solution design, and client discussions when required.Apply responsible AI principles, including security, privacy, governance, human oversight, and cost control.Contribute to reusable AI components, frameworks, and delivery acceleratorsCandidate ProfileStrong hands-on experience delivering AI, ML, data-science, or data-engineering solutions.Experience taking AI or ML solutions beyond proof-of-concept into production or production-like environments.Strong Python skills and good software engineering fundamentals.Experience with machine learning techniques such as classification, regression, forecasting, clustering, anomaly detection, optimisation, or segmentation.Experience with generative AI, LLMs, RAG, prompt engineering, tool use, or agentic workflow design.Good understanding of data pipelines, APIs, cloud-native architectures, and CI/CD.Experience with model evaluation, monitoring, versioning, and deployment.Comfortable working in client-facing or consultancy environments.Able to communicate clearly with both technical and non-technical stakeholders.

Technical Skills

Python, Pandas, NumPy, Scikit-learnXGBoost, LightGBM, CatBoost, Statsmodels, forecasting or optimisation librariesOpenAI, Azure OpenAI, Anthropic, AWS Bedrock, Google Vertex AI, or similarLangChain, LangGraph, Semantic Kernel, LlamaIndex, AutoGen, CrewAI, or similarVector databases such as Pinecone, Weaviate, Milvus, pgvector, Azure AI Search, or similarMLflow, Databricks, Unity Catalog, Databricks Model Serving, Feature Store, or FeastSnowflake, Delta Lake, Apache Spark, Kafka, Confluent Cloud, Airflow, or Databricks WorkflowsAzure, AWS, or GCPDocker, Kubernetes, REST APIs, CI/CD, TerraformMonitoring and observability tools such as Prometheus, Grafana, ELK, or OpenTelemetry