Group Senior AI Engineer at Salt South Africa

• Imagine a global consumer brand with big ambitions and a huge digital footprint – think thousands of daily interactions, loads of behavioural data, and teams across multiple continents all hungry for smarter, faster, AI‑powered ways of working.
• They’re not dipping a toe into AI. They’re scaling it – responsibly, safely, and with real momentum. Which is why they need a Senior AI Engineer who can own delivery, navigate ambiguity, and raise the bar for everyone around them.

What You’ll Be Doing

• This is the senior-level version of an AI Engineer: same end‑to‑end ownership, but with more leadership, more influence, and bigger, messier, more rewarding problems.

You’ll:

• Take full technical ownership of AI systems – from prototype to production reliability.
• Make architectural calls that balance speed, stability, and long-term maintainability.
• Convert loosely defined business questions into clear AI solutions with measurable impact.
• Build everything from classical ML models to LLM-powered services (RAG, fine-tuning, adapters, you name it).
• Deeply integrate your models into apps, CRM platforms, workflows, digital journeys, and internal tools.
• Lead experiments, run A/B tests, validate hypotheses, and guide stakeholders through trade‑offs.
• Set up monitoring, drift checks, retraining flows, observability, and proper MLOps hygiene.
• Work hands-on with data, modelling, pipelines, APIs, orchestration – the full engineering spectrum.
• Mentor juniors, shape engineering standards, and help create reusable blueprints for future AI builds.
• Act as a champion for safe, transparent, responsible AI use.
• If you like being the person who steps into complexity, simplifies it, owns it, and ships something solid – good news: you’ve found your people.

Who You Are
You don’t need to match every bullet, but you’re likely to thrive if you’re someone who:

• Has roughly 8+ years working in ML, data science, or software engineering with real AI ownership.
• Has shipped multiple AI/ML systems into production – not just POCs.
• Has led at least one meaningful end‑to‑end AI initiative (technical direction + stakeholder alignment).
• Is comfortable with Python + SQL and enjoys writing clean, production-level code.
• Knows ML frameworks (scikit‑learn, XGBoost, PyTorch, TensorFlow, LightGBM etc.).
• Has experience with LLMs and generative AI (APIs, RAG, evaluation, tuning).
• Understands data engineering basics and can work with pipelines, warehouses, and orchestration tools.
• Is familiar with the cloud (Azure, AWS, or GCP all welcome).
• Navigates ambiguity well – shaping scope instead of waiting for it.
• Communicates clearly, especially with non‑technical stakeholders.
• Loves mentoring, pair programming, reviewing code, and raising team standards.
• Understands privacy, safety, and the need for responsible AI.
• Values outcomes over grand ideas.