South Pole Logo

South Pole

Senior Lead, AI Engineering, GDBS

Posted One Month Ago
Be an Early Applicant
Hybrid
London, Greater London, England, GBR
Senior level
Hybrid
London, Greater London, England, GBR
Senior level
Design, build, and ship production-grade LLM-powered features (RAG, extraction, summarisation, agentic tooling). Build data and inference pipelines, integrate with back-ends and vector stores, ensure evaluation, monitoring, cost and performance optimisations, and champion testing and reliability alongside product and tech leads.
The summary above was generated by AI

South Pole is an energetic, global company offering comprehensive sustainability solutions and services. With offices spanning all continents across the globe, we strive to create a sustainable society and economy that positively impacts our climate, ecosystems and developing communities. With our solutions, we inspire and enable our customers to create value from sustainability-related activities.

Our Corporate Functions team is the “enablement engine” of South Pole. Behind the scenes, we provide the business with world-class solutions and best practices that sustain business growth and success. We cover key areas such as Finance, HR, Office Management, Legal, IT, Operations, etc. If you are a smart, ambitious and dynamic professional with a strong passion to make a real difference in the fight against climate change, the below position may be right for you!

Job summary:

South Pole is looking for an AI Developer to help build the intelligent layer behind our products. You will design, build, and ship production-grade AI features: LLM-powered workflows, retrieval pipelines, and agentic tooling that turn large, messy environmental and carbon-market data into reliable answers.

This is a hands-on engineering role pitched at a medior-to-senior level. We are open to a strong medior developer ready to step up, as well as a senior who can take a vague requirement and turn it into a tested, well-reasoned feature. What matters is that you understand the why behind your choices - not just how to call an API, but when not to, and how to keep an AI system trustworthy, evaluated, and cost-aware in production. 

Key Responsibilities:

  • AI Feature Development: Design and ship LLM-powered features end to end - retrieval-augmented generation (RAG), structured extraction, summarisation, and agentic / tool-using workflows.

  • Pipelines & Integration: Build robust data and inference pipelines that connect our AI layer to product back-ends, vector stores, and source systems (AQ, Salesforce, Google Workspace).

  • Evaluation & Reliability: Stand up evaluation, monitoring, and guardrails so AI features are measurably accurate, safe, and stable - not just impressive in a demo.

  • Performance & Cost: Optimise latency, token usage, and throughput; apply caching, batching, and model-routing to keep large workloads fast and economical.

  • Quality Assurance: Champion rigorous testing and pull-request discipline to prevent regressions and keep deployments stable.

  • Collaboration: Partner with the Tech Lead and product owners to translate business problems into AI solutions, and flag where a non-AI approach is the better call.

Technical Requirements - Core Stack

AI & Machine Learning

  • 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.

  • 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.

  • Evaluation: Awareness of LLM evaluation, hallucination mitigation, and basic red-teaming of AI outputs.

Back-end & Data

  • Back-end: Strong Python (FastAPI / Flask / Django), with clean, testable, production-oriented code.

  • Database: Solid PostgreSQL - comfortable with relations, indices, constraints, and transactions beyond basic ORM usage.

  • Data: Experience handling large, high-volume datasets and streaming / batch processing.

Systems & Cloud-Native Architecture

  • Cloud: Experience with GCP (Vertex AI, Cloud Run, Pub/Sub) or a comparable cloud platform.

  • Event-Driven Design: Proficiency with queues and Pub/Sub for asynchronous, event-driven workflows.

  • DevOps Fundamentals: Working knowledge of CI/CD workflows and containerisation (Docker; Kubernetes a plus).

  • Security: Sound practices around authentication, authorisation, throttling, and handling of sensitive and proprietary data in AI workflows.Systems & Cloud-Native Architecture

  • Cloud: Experience with GCP (Vertex AI, Cloud Run, Pub/Sub) or a comparable cloud platform.

  • Event-Driven Design: Proficiency with queues and Pub/Sub for asynchronous, event-driven workflows.

  • DevOps Fundamentals: Working knowledge of CI/CD workflows and containerisation (Docker; Kubernetes a plus).

  • Security: Sound practices around authentication, authorisation, throttling, and handling of sensitive and proprietary data in AI workflows.

Communication Skills:

  • Proficiency in business English.

  • Ability to translate complex technical and AI concepts into understandable terms for non-technical business colleagues.

Desirable Requirements:

  • 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.

The Ideal Candidate Profile:

  • 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.

What we offer:

At South Pole, we care about our employees as much as we care about the planet. South Pole is not just an employer, we are a Team. South Pole does not just offer people a job, we offer you a career. By joining our team, you will find strong purpose and deep meaning in everything you do. You will have the chance to make a real difference for our clients and for the planet, working alongside a passionate team of like-minded colleagues, while building your knowledge/skills and developing your career in a fun, dynamic, international and fast-growing organisation. 

We’re a planet of 7.5 billion unique and different people. We all have a contribution to make and South Pole is proud to be an Equal Opportunity Employer. We do not discriminate on the basis of race, religion, colour, sex, gender identity, sexual orientation, age, national origin, marital status or disability. Our recruitment is decided on the basis of qualifications, merit and business need.

Similar Jobs

Senior level
Artificial Intelligence • Healthtech • Machine Learning • Natural Language Processing • Biotech • Pharmaceutical
Leads health technology assessment, value, and evidence strategy for Pfizer’s genitourinary oncology portfolio. Manages HEOR, real-world evidence, economic models, global value dossiers, registries, and evidence dissemination to support reimbursement and patient access. Partners with global, regional, country, and cross-functional oncology teams, oversees vendors and project teams, and communicates findings through publications and conferences.
2 Days Ago
Hybrid
Internship
Internship
Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
Supports strategic consulting projects for major clients across industries. Responsibilities include analyzing data, identifying trends, developing recommendations, creating client presentations, structuring business problems, collaborating in small teams, and building client relationships. Interns may specialize in Strategy & Transformation or Performance Analytics while receiving mentorship, networking, and professional development opportunities.
Top Skills: Business Intelligence PlatformsExcelPythonSASSQLTableau
2 Days Ago
In-Office or Remote
Senior level
Senior level
Artificial Intelligence • Healthtech • Machine Learning • Natural Language Processing • Biotech • Pharmaceutical
Provides technical leadership for Python-based AI backend platforms supporting LLM integrations, generative AI pipelines, and agent orchestration. Architects scalable AWS systems using FastAPI, Lambda, and EKS; establishes observability and engineering standards; drives performance, security, and reliability improvements; mentors engineers; and influences organization-wide technical strategy, platform capabilities, and best practices.
Top Skills: Amazon EksAnthropic ApiAWSAws LambdaCi/CdDistributed SystemsDockerEvent-Driven ArchitectureFastapiInfrastructure As CodeKubernetesLangchainLangfuseLitellmMicroservicesMlopsOpenai ApiPython

What you need to know about the London Tech Scene

London isn't just a hub for established businesses; it's also a nursery for innovation. Boasting one of the most recognized fintech ecosystems in Europe, attracting billions in investments each year, London's success has made it a go-to destination for startups looking to make their mark. Top U.K. companies like Hoptin, Moneybox and Marshmallow have already made the city their base — yet fintech is just the beginning. From healthtech to renewable energy to cybersecurity and beyond, the city's startups are breaking new ground across a range of industries.

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account