AI Engineer; LLMs & Agents

Are you passionate about leveraging AI to transform global industries? Do you have experience working with LLMs and building agentic solutions?

Join Elixirr Digital as an AI Engineer, where you will drive innovation and help shape the future of intelligent systems for clients across industries like banking, insurance, healthcare, telecommunications, consumer goods, and more. We're looking for proactive self-starters who are constantly reading research, applying it, and using AI to improve their processes, fully embracing the technology.

At Elixirr Digital, we've been on the cutting edge of generative AI from the beginning, developing our own platforms and deploying transformative solutions to global clients for several years. Our expertise spans working with frontier and open-source models across providers including Anthropic, OpenAI, Google, and Meta, and leading frameworks like Lang Chain, Google ADK, and Auto Gen to build innovative, agentic solutions built on open standards like the Model Context Protocol (MCP).

From underwriting agents that empower financial professionals to knowledge agents streamlining customer workflows, our solutions are revolutionizing industries by embedding AI at their core.

If you're excited to work at the forefront of generative AI, helping enterprises transform from the inside out, we want to hear from you. Let's build the future of AI together!

Candidates applying, kindly note that we are also considering the wider surrounding areas of Johannesburg and Cape Town for this position.

What will you be doing as an AI Engineer at Elixirr Digital?

• Design and Implement Solutions: Architect, design, and develop advanced AI systems with a focus on LLMs and agentic solutions, including tool integration, retrieval-augmented generation, and memory-augmented workflows that transform enterprise processes.
• Collaborate: Work closely with cross-functional experts, senior engineers, and clients to deliver AI-driven innovations.
• Drive Innovation: Work on a mix of internal R&D projects and enterprise-level solutions, building and optimizing tools for both internal and client use.
• Deploy at Scale: Develop and maintain production-ready AI solutions, ensuring scalability, performance, reliability, and observability through tracing and evaluation tooling.
• End-to-End Lifecycle: Contribute to the entire AI development lifecycle, from research and prototyping to deployment, monitoring, and continuous improvement.
• Deliver Tangible Outcomes: Help global enterprises achieve measurable impact through solutions like underwriting agents, airport assistants, pharmacy workflow optimizers, and customer due diligence systems.

Competencies and skillset we expect you to have to successfully perform your job:  

• Have Experience with LLMs and Agents: Hands-on experience building agentic solutions using frameworks such as Lang Chain, Google ADK, or Auto Gen, and growing familiarity with open standards like the Model Context Protocol (MCP). Experience integrating tools, managing context, and working with retrieval pipelines.
• Bring Technical Expertise: Solid background in programming and foundational experience in machine learning, with working knowledge in at least one area such as deep learning, fine-tuning, or RAG-based architectures.
• Think Analytically: Strong problem-solving and critical thinking skills, with the ability to translate complex requirements into well-structured AI solutions. Comfortable applying mathematical principles to model and solve real-world problems.
• Focus on Outcomes: Passion for transforming businesses and delivering measurable results through AI.
• Collaborate Effectively: Experience working in cross-functional teams, balancing R&D and production-level work.
• Embrace AI-Native Development: Comfortable using AI-assisted coding tools such as Claude Code, Cursor, or Git Hub Copilot as part of your daily workflow, with good judgment about when to trust and when to verify AI-generated output.
• Care About Quality: Familiarity with testing and evaluating LLM outputs, using logging or tracing tools to debug and improve system behaviour in production.
• Are Innovation-Driven: Stay ahead of AI trends,…