Senior AI Engineering Lead (GDBS)

Join South Pole, a leading climate action company, as a Senior AI Engineering Lead. In this hands-on engineering role, you will design, build, and ship production-grade AI features that turn large environmental and carbon-market data into reliable answers. You will work closely with the Tech Lead and product owners to translate business problems into AI solutions. The position offers flexible working hours, above-average vacation allowances, life insurance, and access to mental, physical, and financial wellbeing support.

• Design, build, and ship production-grade AI features, including LLM-powered workflows and retrieval pipelines.
• Build robust data and inference pipelines that connect the AI layer to product back-ends, vector stores, and source systems.
• Stand up evaluation, monitoring, and guardrails so AI features are measurably accurate, safe, and stable.
• LLM Engineering: Hands-on experience building with LLM APIs (e.g. Anthropic, OpenAI, or Vertex AI / Gemini) - prompt design, function/tool calling, and structured outputs
• Evaluation: Awareness of LLM evaluation, hallucination mitigation, and basic red-teaming of AI outputs
• RAG & Retrieval: Practical knowledge of embeddings, chunking, and vector search (pgvector, or a managed vector DB)
• Frameworks: Familiarity with at least one orchestration framework (LangChain, LlamaIndex, or equivalent), and comfort working without one when it's simpler
• Data: Experience handling large, high-volume datasets and streaming / batch processing
• Database: Solid PostgreSQL - comfortable with relations, indices, constraints, and transactions beyond basic ORM usage
• Back-end: Strong Python (FastAPI / Flask / Django), with clean, testable, production-oriented code
• DevOps Fundamentals: Working knowledge of CI/CD workflows and containerisation (Docker; Kubernetes a plus)
• Cloud: Experience with GCP (Vertex AI, Cloud Run, Pub/Sub) or a comparable cloud platform
• Security: Sound practices around authentication, authorisation, throttling, and handling of sensitive and proprietary data in AI <workflows.Systems> & Cloud-Native Architecture
• Event-Driven Design: Proficiency with queues and Pub/Sub for asynchronous, event-driven workflows
• Security: Sound practices around authentication, authorisation, throttling, and handling of sensitive and proprietary data in AI workflows
• Proficiency in business English
• Ability to translate complex technical and AI concepts into understandable terms for non-technical business colleagues
• Experience with MLOps / model lifecycle tooling, or fine-tuning
• Exposure to front-end work (React / Next.js) for AI-facing interfaces
• Interest in climate, carbon markets, or sustainability data
• Proactive Communicator: You are proactive and communicative. In interviews you prefer a conversational approach - walking us through your reasoning and the trade-offs behind your tech choices, rather than just providing the “correct” answer
• Pragmatic Problem Solver: You don't just make a model work once; you find the root cause, build for reliability, and know when a simpler, non-AI solution is the right one
• Independent: You can take a high-level requirement and turn it into a fully functional, tested, evaluated feature with minimal oversight
• Responsible by Default: You care about accuracy, safety, cost, and the trustworthiness of what you ship - a natural fit for a climate company where credibility matters