AI Operations & Strategy Engineer

Job Description

About us:

Social Places is an award-winning marketing technology agency based in Century City, Cape Town. Since 2015, we have developed proprietary marketing and CRM software that enables our clients to manage their digital ecosystem seamlessly across multiple platforms from a single dashboard. Operating in 49+ countries, we are proud to serve some of the world’s largest franchise brands.

Our team of 60 talented, driven professionals thrives in a dynamic, flexible working environment. As we continue to scale globally, we are looking for ambitious individuals to join us on this journey.

Role Description:

We are looking for a skilled and strategically-minded AI Operations & Strategy Engineer to join our senior engineering team and report directly to the CTO and Technical Lead. You will be the crucial custodian of our AI/LLM strategy, driving adoption, managing costs, ensuring ethical and reliable output, and shaping our future AI product direction.

You'll operate within a dynamic Agile environment with one-week sprints and bi-weekly retrospectives, where your AI expertise will directly impact our business KPIs and OKRs.

What you will be doing:

AI Governance & Prompt Management: Design, implement, and manage a centralised repository for all production AI prompts, ensuring optimal performance, consistency, and alignment with brand voice(s). This includes version control and iterative refinement of prompt engineering strategies to maximise output quality and efficiency.

Cost Management & Optimisation (AI FinOps): Proactively monitor, track, and implement strategies to ensure efficient use of resources across all AI integrations (e.g., OpenAI, Google, AWS services). This involves analysing token usage, optimising model selection, and balancing performance requirements with cost-effectiveness to maintain a high ROI for AI features.

Evaluation Frameworks & Assurance: Develop and enforce rigorous evaluation metrics and frameworks (e.g., RAG-specific metrics, human-in-the-loop validation) to consistently measure the accuracy, reliability, and fairness of AI outputs. You will report on AI performance and drive remediation where necessary.

Internal AI Enablement & Support: Act as the internal champion for AI tools. You will train, assist, and advise all team members (Product, QA, UI/UX, Engineering) on the most effective and responsible use of AI tools integrated into our workflow or used for internal productivity.

AI Strategic Roadmap Contribution: Work closely with the Product and Engineering leads to identify, research, and prototype new AI features, models, and integrations. You will contribute to the technical specifications and future-proofing of our AI capabilities, ensuring we remain at the cutting edge of AI-enhanced SaaS.

Documentation & Knowledge Sharing: Create and maintain high-quality documentation for AI frameworks, prompt guidelines, best practices, and governance policies. You will participate in formal handovers and retrospectives to capture and apply lessons learned from AI deployments.

Collaboration: Work closely with the senior engineers and product team in daily standups and throughout the sprint cycle, providing expertise on AI model integration, prompt effectiveness, and ethical AI deployment.

What you will bring:

Essential Qualifications

Proven experience as an AI Engineer, Machine Learning Engineer, or similar role focused on LLM operations and governance.

Expert-level proficiency in Prompt Engineering, including experience with advanced techniques for optimising LLM performance, consistency, and cost.

Strong understanding of various AI/ML models, their APIs (e.g., OpenAI, Anthropic, Gemini), and the ability to select the right model for the right task.

Experience in designing and implementing evaluation frameworks (e.g., RAG evaluation, human scoring, automated testing) for measuring AI output quality at scale.

Solid experience with version control systems (Git) and documentation of AI components.

Excellent problem-solving skills, a proactive attitude, and the ability to work effectively in a collaborative, senior team environment.

Bonus Points for Experience with:

Implementing MLOps practices (CI/CD for models, feature stores, monitoring drift).

Experience with cloud-based AI services (e.g., AWS SageMaker, Google Vertex AI).

Knowledge of ethical AI principles and frameworks for bias detection and mitigation.

Scripting/programming languages for AI/ML development (e.g., Python).

What we offer:

Opportunity to work on exciting and challenging projects

A collaborative and supportive work environment

Continuous learning and professional development opportunities

Flexible working hours

18 leave days per annum

36 days sick leave in a 3-year cycle

1 Extra Annual leave day on each work anniversary

1 Cake day for your birthday (per year)

1 Wedding day

1 Pet day