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Open nowFirst seen 3 hours ago

Ai Engineer

Liquid Thought60 open roles

Where
Cape Town, Western Cape, South Africa
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Your applicationOpen nowAi EngineerLiquid Thought · Cape Town, Western Cape, South Africa

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Share of postings closed within
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  2. 4.4%3 days
  3. 11.5%7 days
  4. 18.1%14 days
  5. 35.6%30 days
  6. 44.6%60 days
This job: first seen 3 hours ago

The posting

AI ENGINEER

Full time

Location: Cape Town, South Africa

Hybrid: 3days per week in office

THIS IS NOT A FULL-TIME REMOTE ROLE, ITS A HYBRID ROLE WITH CAPE TOWN OFFICE ATTENDANCE 3 DAYS A WEEK

Our client, a Cape Town based business operating in the fintech space, is focused on changing how people access and experience financial services. With ambitious growth plans ahead, they are building their AI capability and putting AI at the centre of how the business operates and serves its customers.

Main purpose of the role

Our client is looking for an experienced AI Engineer to join their team and help bring artificial intelligence into the products, platforms and processes that power the business. In this role, you'll design, build and deploy production AI solutions that add real value to customer experiences, operations and decision making.

You'll take ownership of challenging problems, from personalisation and fraud detection to LLM powered assistants and automated workflows. You'll collaborate with product owners, engineers, data specialists and business teams to deliver AI solutions that make a measurable difference for the business and its customers, working closely with the Chief Technology and Information Officer.

Key responsibilities

1. AI production and delivery

  • Design, develop and deploy AI/ML solutions and pipelines using cloud infrastructure (AWS, Google Cloud, Azure)
  • Build and maintain production machine learning models that power features across the company's platforms and products
  • Implement MLOps practices including model versioning, automated testing, monitoring and continuous deployment
  • Optimise model performance, latency and cost for production environments

2. Applied AI for financial services

  • Build personalisation and recommendation features that improve customer engagement and experience
  • Develop models that support use cases such as fraud detection, risk assessment and customer insight
  • Develop NLP solutions such as document processing, content classification, semantic search and intelligent tagging
  • Integrate large language models (LLMs) and generative AI into products and internal tools, including customer service assistants, summarisation and process automation
  • Work with vector databases and embedding based search to build retrieval and matching solutions

3. Responsible AI and compliance

  • Apply responsible AI practices, including bias testing, explainability and appropriate human oversight
  • Ensure AI solutions meet security, data privacy and POPIA requirements, as well as applicable financial services regulations
  • Support AI governance by documenting models, data sources, risks and controls

4. Business and product collaboration

  • Work with multidisciplinary teams to turn business requirements into practical AI solutions
  • Help scope AI features and explain technical options and trade offs to stakeholders without a technical background
  • Contribute to proofs of concept that help the business explore where AI can add the most value

5. Technical excellence and innovation

  • Write clean, maintainable and well documented Python code, following software engineering best practices
  • Design and implement APIs and microservices for AI model serving and integration
  • Experiment with LLMs, transformer architectures and generative AI
  • Stay current with AI/ML developments and share new approaches with the team

6. Collaboration

  • Participate in code reviews, technical discussions and architecture conversations
  • Support junior team members through code reviews and knowledge sharing
  • Collaborate with data scientists and engineers to take prototypes into production

Required skills and experience

a) Technical qualifications

  • Degree in Computer Science, Machine Learning, Data Science or a related technical field (Honours or Masters advantageous)
  • 3 to 5 years of software engineering experience, with at least 2 years focused on AI/ML development
  • Strong proficiency in Python and experience with ML frameworks (TensorFlow, PyTorch, scikit learn)
  • Hands on experience with cloud platforms (AWS SageMaker, Google AI Platform, Azure ML) and Docker
  • Demonstrable experience building and deploying ML models in production

b) AI/ML expertise

  • Strong understanding of machine learning algorithms, deep learning architectures and neural networks
  • Experience with NLP, text processing and recommendation systems
  • Working knowledge of MLOps practices, including model monitoring, versioning and retraining
  • Familiarity with vector databases, embedding based search and similarity matching
  • Familiarity with transformer models, large language models and modern NLP architecture
  • An understanding of the risks associated with AI in a regulated environment, including bias, data privacy and security

c) Software engineering

  • Experience with API development (REST, GraphQL) and microservices
  • Experience with Git, CI/CD pipelines and automated testing frameworks
  • Good understanding of database technologies (SQL, NoSQL) and data pipeline tools
  • Knowledge of software engineering best practices, including design patterns and code quality standards

Preferred experience

  • Experience in fintech, banking, payments or financial services
  • Experience with fraud detection, risk models or credit related use cases
  • Experience with Kubernetes in production
  • Understanding of web analytics, user behaviour analysis and A/B testing
  • Experience with real time streaming data processing (Kafka, Kinesis, Pub/Sub)
  • Familiarity with monitoring and observability tools (Prometheus, Grafana, DataDog)
  • Experience working with Jira and GitHub

Personal characteristics

  • Driven by innovation: passionate about exploring new AI technologies and finding creative solutions
  • Collaborative: able to work across multidisciplinary teams and explain technical concepts to people without a technical background
  • Focused on results: committed to delivering measurable impact for the business and its customers
  • Continuous learner: keeps up with the fast moving AI/ML landscape
  • Problem solver: analytical, with the ability to break complex challenges into manageable parts
  • Quality conscious: attentive to detail and committed to building robust, secure, scalable and maintainable systems
  • Responsible: understands the importance of trust, privacy and ethics when applying AI in financial services

What's on offer

  • A competitive salary, commensurate with your experience and skills
  • High impact work: bringing AI into products and services that change how people access and experience financial services
  • Real ownership, taking solutions from idea through to production and seeing the difference they make for customers
  • The chance to help shape how AI is applied in a growing fintech business, from the ground up
  • A collaborative, innovation focused environment where new ideas are welcomed, tested and built on

Due to the high volume of applications we receive, we are unable to respond to each candidate individually. If you have not heard from us within one month of applying, please consider your application unsuccessful.

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