Expert AI Engineer

About

You will lead the engineering and architectural direction for AI and Machine Learning services, ensuring they are seamlessly integrated into the group's global production processes.

Role & Responsibilities

• AI Architectural Lead: Design and implement end-to-end AI/ML architectures, focusing on scalability and the reuse of services across multiple global domains.
• AWS Production Specialist: 10+ years of hands-on experience in AI/ML engineering, with at least 3 years specifically dedicated to deploying and operating models in AWS production environments.
• Technical Mentor: Act as a senior influence, running training programs and mentoring junior team members to elevate the collective technical capability of the Hub.

Contract Details

• Contract Dates: 01-07-2026 to 31-12-2028
• Location: Midrand/Menlyn/Rosslyn/Home Office Rotation
• Level: Expert
• Experience: 10+ years

Qualifications & Experience

• Education: Degree in Computer Science, Math, Statistics, or Engineering; MSc or PhD is preferred.
• Core Experience: Minimum 10 years of hands-on experience in AI/ML engineering and architecture.
• Cloud Focus: At least 3 years specifically deploying and operating models in AWS production environments.
• Leadership Track Record: Proven history of running training programs and influencing technical direction across teams.

Essential Skills & Technologies

• Deep AI/ML Theory: Comprehensive understanding of classical algorithms (supervised/unsupervised), probabilistic models, Bayesian methods, and optimization techniques.
• AWS Production Engineering: Strong experience implementing models in live environments using AWS SageMaker, EC2, Lambda, and EKS.
• Programming & ML Libraries: High proficiency in Python and the core stack: NumPy, SciPy, scikit-learn, TensorFlow/PyTorch, and XGBoost/LightGBM.
• Software Engineering Excellence: Professional-grade skills in code quality, unit testing, CI/CD, and version control (Git).
• Validation & Evaluation: Proven expertise in bias detection, model calibration, robustness testing, and validation.
• Data & Feature Engineering: Extensive experience with ETL and data pipelines using AWS Glue, Redshift, RDS, and S3.
• End-to-End Architecture: Ability to design entire AI solutions including model serving, inference scaling, and monitoring/observability.
• Technical Mentorship: Proven ability to coach junior engineers/data scientists and lead workshops or code reviews.
• Communication: Exceptional skill in translating technical concepts for business stakeholders and producing high-quality design documentation.
• Governance & Security: Awareness of data privacy (access control, model governance) and implementing security controls within AWS.

Advantageous Skills

• Advanced MLOps: Hands-on experience with SageMaker Pipelines, MLflow, Kubeflow, or TFX.
• Advanced Tooling: Knowledge of probabilistic programming (Pyro, Stan) and XAI techniques (SHAP, LIME).
• Modern Infrastructure: Experience with Docker, Kubernetes (EKS), and real-time streaming data (Kinesis, Kafka).
• Cost Optimization: Experience with spot instances, autoscaling, and model shards for cost-optimized inference.
• Regulatory Knowledge: Familiarity with GDPR and privacy-preserving ML (differential privacy, federated learning).
• Certifications: AWS Certified Machine Learning Specialty or Solutions Architect.

Role & Responsibilities

• Architectural Leadership: Lead the design and delivery of scalable, production-ready AI solutions on AWS, emphasizing classical AI techniques.
• Best Practice Enforcement: Define standards for the entire ML lifecycle from development and validation to deployment and monitoring.
• Pipeline Construction: Build and maintain end-to-end data and model pipelines ensuring they are reproducible and maintainable.
• Inference & Scaling: Drive decisions on model serving strategies, including rollback plans and cost optimization.
• Production Oversight: Oversee model versioning, drift detection, and alerting for live systems.
• Upskilling & Coaching: Mentor junior staff through pair programming, technical reviews, and coaching on skills roadmaps.
• Review and approve technical designs and code from the team to ensure they meet security and engineering standards.
• Partner with product managers to translate complex business problems into well-scoped ML solutions.
• Ensure all models are interpretable, fair, and compliant with global regulatory requirements.

Notes

• South African citizens or residents are preferred. Applicants with valid work permits will also be considered.
• By applying, you give iSanqa consent to process your personal information as per the POPI Act.