1154 AI Engineer (Advanced), Menlyn

Description

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
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:

Responsibilities include:
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)
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:

Submit your CV to: and Subject line Role title

Highlights

Safety Tips

Do not pay a ’prospective employer’ anything in order to secure a job.