AI & Automation Tech Lead - Build Scalable, Secure Systems

CyberPro Consulting (Pty) Ltd

Cape Town

On-site

ZAR 1,200,000 - 2,100,000

Full time

2 days ago

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Job summary

CyberPro Consulting (Pty) Ltd in Cape Town seeks a Tech Lead Engineering – AI and Automation to design, develop and deploy AI and automation solutions that boost efficiency, improve customer and employee experiences, and increase operational productivity. You will lead a team of engineers, translate opportunities into secure, scalable production systems and set engineering standards.

The role partners with business, product, data and security teams to govern projects, establish reusable

Qualifications

Degree in Computer Science, Engineering, Information Systems or a related field.
8+ years of software engineering experience, including at least 3 years in a Technical Lead or Team Lead role.
Proven experience delivering AI/ML or Generative AI solutions into production environments.
Demonstrable experience delivering process automation solutions, including RPA, workflow automation or low-code platforms.
Experience working with major cloud platforms such as Microsoft Azure or AWS.
Relevant cloud certification (Azure or AWS) is advantageous.
Financial services or insurance industry experience is advantageous.
Strong software engineering skills in Python and at least one of C#, Java or TypeScript, including API design and microservices architecture.
Hands-on experience with LLMs and Generative AI, including prompt engineering, RAG, vector databases, agent orchestration and evaluation frameworks.
Experience with automation and orchestration platforms such as UiPath, Microsoft Power Automate or similar technologies.
Cloud-native development and AI services on major cloud platforms, including containers, DevOps and CI/CD.
Strong understanding of data engineering fundamentals, including data pipelines, data quality and structured and unstructured data.
Knowledge of AI security and governance, including identity and access management, data protection, model risk and POPIA compliance.
Strong solution architecture and design capabilities, with the ability to assess build, buy and reuse opportunities.
Proven leadership experience managing cross-functional engineering teams and influencing senior stakeholders.
Excellent communication, problem-solving and stakeholder management skills.

Responsibilities

Lead, coach and develop a team of AI, automation and software engineers, including recruitment, performance management and skills development.
Define and maintain engineering standards, reference architectures and reusable components for AI and automation solutions.
Design and develop solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents and integrations with enterprise systems and APIs.
Drive intelligent automation of business processes, including workflow automation, RPA and intelligent document processing.
Take solutions from proof of concept to production, ensuring they are secure, scalable, observable and supportable.
Establish MLOps/LLMOps practices, including CI/CD, model and prompt versioning, automated evaluation, monitoring and cost tracking.
Implement responsible AI controls, including human-in-the-loop design, guardrails, accuracy and bias testing, explainability and audit trails.
Ensure compliance with AI governance frameworks, POPIA and relevant regulatory requirements.
Partner with business units and product owners to identify, assess and prioritise AI and automation opportunities based on business value, feasibility and risk.
Collaborate with enterprise architecture, data, security and infrastructure teams to ensure seamless integration with core systems and cloud platforms.
Identify opportunities to leverage shared platforms, reusable components and emerging technologies.
Evaluate AI and automation tools and platforms, and manage relationships with technology vendors and partners.
Monitor and report on delivery progress, solution adoption and business benefits realised, including productivity improvements, reduced turnaround times and cost savings.
Stay informed of emerging AI and automation trends to influence technology strategy and innovation.
Build AI literacy and engineering capability through knowledge sharing, technical demonstrations, mentoring and communities of practice.