AI Engineer (Entry)
Full-time
Imizizi
Reference: JHB001458-ZN-1 ESSENTIAL SKILLS
- Large Language Models (LLMs), RAG systems, multi agent frameworks (LangChain, LangGraph, GAIA)
- Python (Advanced), ML engineering (TensorFlow, PyTorch, Scikit learn)
- Vector Databases (FAISS, Pinecone, Elasticsearch/OpenSearch)
- Prompt Engineering & Context Orchestration
- MLOps (SageMaker, ML Pipelines, GitHub Actions, CI/CD)
- AWS AI/ML stack: SageMaker, Lambda, Step Functions, API Gateway, DynamoDB, S3
- Data Engineering: Spark, Kafka, SQL/NoSQL, ETL/ELT
- Docker, Kubernetes (EKS), Terraform
- Cloud Observability: CloudWatch, X Ray, logging/monitoring
- API & Microservices development
- Cloud Data Hub (CDH), CDEC Integration
- Experience with Confluence, JIRA, and creating technical documentation
- Understanding of data governance, AI risk, security, compliance, and IAM
- Basic experience/understanding of AWS Components (in order of importance):
- Glue, Kinesis (Streams & Firehose), Redshift, Athena, SNS, SQS, Secrets Manager, Param Store, CloudFormation.
ADVANTAGEOUS SKILLS
- Experience building production grade AI systems (RAG, agents, embeddings, search)
- Strong mathematical foundations in probability, optimization & deep learning
- AI cost optimization and performance tuning
- Experience with graph based reasoning, semantic caching, and model evaluation strategies
- Strong communication skills for translating business needs into AI architectures
- Ability to design AI safety controls and ensure model reliability
- Experience preparing architectural specifications, solution designs and PoC to production handover
- Strong organisational skills and ability to lead technical streams
ROLE & RESPONSIBILITIES
- AI Engineers are responsible for designing, building, and operationalising AI systems that scale across clients platforms.
- Build enterprise grade AI/ML systems (LLMs, RAG, multi agent automation, vision/NLP models)
- Develop retrieval pipelines, embedding strategies, semantic indexes & vector search
- Build and maintain cloud native AI workflows using AWS (SageMaker, Lambda, EMR, Step Functions)
- Integrate AI solutions into clients' platforms (CDEC, CDH, SAP, microservices)
- Lead PoCs, architecture designs, and collaborate with global stakeholders
- Implement MLOps pipelines & model monitoring (drift detection, auto retraining)
- Ensure security alignment, model governance, responsible AI practices
- Document designs, decisions, evaluations, and solution patterns
- Support Agile ceremonies, sprint planning, backlog refinement and cross team collaboration
QUALIFICATIONS/EXPERIENCE
- Relevant IT / Engineering / Computer Science / Data Science Degree
- AWS ML Specialty
- AWS Solutions Architect (Associate/Professional)
- DeepLearning.AI (GenAI, LLMs, Agents)
- Hashicorp Terraform Associate
Submit your CV to: and Subject line
Role title
Vacancy posted 29 days ago
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