Associate AI Solutions Engineer

Sanlam Limited; Bellville; Hybrid; ZAR 350,000 - 600,000; Full time

Job summary

Sanlam Life and Savings is seeking a hybrid ML/DevOps/AI Engineer to help build production-ready ML pipelines on AWS. You will work with Data Scientists and AI Solutions Engineers, progressing from foundational to intermediate and senior levels in ML, GenAI, and cloud engineering.

You’ll contribute to data preprocessing, model evaluation, and deployment, with a focus on MLOps hygiene and collaboration across cross-functional teams.

Qualifications

• Bachelor’s degree in Engineering, Computer Science, Statistics, Mathematics or related field.

Responsibilities

• Data preprocessing and feature engineering; build, tune and evaluate ML models.

Skills

Python programming

Data preprocessing

ML frameworks

Docker

GitHub Actions / GitLab CI

AWS cloud services

SQL

Communication

Education

Bachelor’s degree in Engineering, Computer Science, Statistics, Mathematics

Tools

Docker

AWS

Git

CI/CD pipelines

Job description

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Sanlam Life and Savings (SLS) is focused on serving our retail and corporate clients in South Africa and further developing our strategic advantages in the South African market.Sanlam Life and Savings consists of the following business units Retail Mass, Corporate, Risk and Savings, Glacier and various business enabling functions. The Sanlam Life and Savings Office provides strategic direction, coordination and support to the four clusters, as well as performing governance oversight that includes assurance provided by second line of defense functions in SLS, to enable us to meet our business objectives.

What will you do?

You will join the AI Solutions team, at the forefront of building and deploying data-driven and GenAI-powered solutions across the Sanlam Life & Savings Cluster.
This is a hybrid engineering role, part ML Engineer, part DevOps Engineer, part AI Engineer. You'll help build machine learning and GenAI capabilities and package them into reliable, production-ready pipelines running on AWS. You'll work closely with AI Solutions Engineers, Data Scientists and cross-functional teams, gaining hands-on exposure across the full ML/AI lifecycle, from feature engineering to cloud deployment. You'll work closely with the wider AI Solutions team, Data Scientists, and cross-functional colleagues as you build breadth across ML, GenAI, and cloud engineering. You won't be expected to have deep expertise in all these areas from the start, this is a role designed for hands-on learning, with a structured technical growth framework offering a clear path to Intermediate and Senior levels as your capability develops. This is a fantastic opportunity for someone early in their engineering career who wants to build strong foundations in modern AI infrastructure.

What will make you successful in this role?

Key Responsibilities:

• Data & Model Foundations: Assist in data preprocessing, feature engineering and contributing to shared feature stores. Support the building, tuning and evaluation of ML models using frameworks such as Scikit-learn and PyTorch.
• GenAI & LLM Systems: Gain exposure to LLM fundamentals, prompt engineering and Retrieval-Augmented Generation (RAG) patterns, including working with embeddings and vector search, with support from the wider team.
• MLOps & Deployment: Support the build and maintenance of ML pipelines, training, deployment and monitoring, helping models move from experimentation into production and tracking basic performance and drift metrics.
• Cloud & DevOps: Work with AWS core services (S3, EC2, Lambda, IAM) and containerization tools (Docker) to support deployment. Contribute to CI/CD pipelines and version-controlled workflows (Git) and get exposure to Infrastructure-as-Code concepts.
• Code Quality & Collaboration: Write clean, testable code, participate in code reviews and help establish good MLOps hygiene. Communicate progress and technical trade-offs clearly with the team.
• Continuous Learning: Stay curious. Proactively build knowledge of new tools and trends across ML, GenAI, and cloud engineering.

Qualifications and experience

• Bachelor’s degree in Engineering, Computer Science, Statistics, Mathematics, or a related field.
• Foundational programming experience in Python (OOP, readable code)
• Exposure to SQL, R or Java is advantageous.
• Basic exposure to containerisation (Docker) and CI/CD tools, such as GitHub Actions or GitLab CI, is advantageous.

Knowledge and skills

• Basic understanding of databases and database querying.
• Awareness of AWS (or another cloud provider) core services, such as S3, EC2, Lambda and IAM.
• Familiarity with Git and standard version-control workflows.
• Exposure to ML frameworks (Scikit-learn and PyTorch) and basic hyperparameter-tuning concepts.
• Conceptual understanding of LLMs, prompt engineering and RAG architectures is advantageous.
• Strong analytical and problem-solving skills with attention to detail.
• Excellent written and verbal communication skills, with the ability to engage confidently with technical and non-technical stakeholders.
• A collaborative and team-oriented approach to work.

Personal attributes

• Curiosity: A strong desire to learn and stay updated with the latest trends and advancements in machine learning and AI.
• Creativity: Innovative thinking to develop unique solutions and approaches to complex challenges.
• Persistence: Resilience in troubleshooting issues and iterating on models, understanding that not every approach will yield immediate success.
• Adaptability: Comfort with shifting tools, priorities and techniques in a fast-moving field.
• Pipeline driven mindset: Ability to connect the technical solution dots to achieving a desired end-state.

Core competencies

• Cultivates Innovation
• Client Focus
• Drive Results
• Collaborates
• Flexibility and adaptability

The Sanlam Group is committed to achieving transformation and embraces diversity. This commitment is what drives us to achieve a diverse, inclusive and equitable workplace as we believe that these are key components to ensuring a thriving and sustainable business in South Africa. The Group's Employment Equity plan and targets will be considered as part of the selection process.