Support the design, development, and evaluation of LLM and ML models used for tasks like emissions estimation, document parsing, anomaly detection, and predictive analytics.

Design, build, and optimize AI Harnesses (agent loops, execution layers, memory, and tool integration) to enable LLMs to operate reliably on production workflows.

Analyze user feedback, execution traces, and failed AI Harness rollouts to identify context degradation, tool failures, or reasoning breakdowns.

Build and maintain offline AI evaluation pipelines and test suites (using custom LLM-as-a-judge patterns or eval frameworks) to systematically benchmark performance before deployment.

Engineer, optimize, and structure system prompts, context windows, and tool schemas to prevent context loss and agent thrashing during complex runs.

Design human-in-the-loop fallback mechanisms into agent workflows to smoothly route low-confidence outputs for human review.

Work with structured and unstructured sustainability data (e.g., carbon emissions, energy usage, supply chain reports) to create gold-standard training/eval datasets and validate system performance.

Assist in the implementation of NLP and LLM techniques for ESG reporting automation, taxonomy matching, intelligent data extraction, and RAG pipelines.

Collaborate with product managers, data scientists, and engineers to integrate production-ready AI features into the platform.

Conduct research on recent AI advancements relevant to climate tech, agentic architecture, LLM applications, and environmental data science.

Collaborate with marketing and sales to optimize business development activities and operations based on AI tools.

Document findings, system architectures, and failure analyses to contribute to internal knowledge sharing on AI methods and sustainability-focused use cases.

6-to-12-month internship (minimum 6 months) at 24 hours per week.

Driven self-starter and AI/sustainability allrounder motivated to create measurable impact.

Currently pursuing a degree (BSc, MSc, or PhD) in Artificial Intelligence, Data Science, Machine Learning, Environmental Informatics, or a related field.

Strong foundational knowledge of Python, core data science libraries (Pandas, NumPy, Scikit-learn), and machine learning algorithms.

Fundamental understanding of LLMs, with practical experience building RAG architectures and AI harness solutions.

Familiarity with Test-Driven Development (TDD) principles and using agentic coding tools (e.g., Claude Code) for rapid, robust delivery.

Understanding of AI evaluations (evals) as the primary benchmark for system performance, safety, and reliability.

Experience building and integrating RESTful APIs (e.g., FastAPI, Flask) to connect AI models with external data streams.

Solid proficiency with Git and version control best practices to maintain clean, collaborative codebases.

Understanding and ideally experience with cloud deployment environments (e.g., AWS, GCP, Azure, or serverless setups).

Practical exposure to modern AI frameworks and tools (Gemini, ChatGPT, PyTorch, Hugging Face, LangChain, or LlamaIndex).

Demonstrated interest or coursework in sustainability, climate tech, ESG reporting, or environmental data.

Bonus: Practical experience with key sustainability frameworks (GHG Protocol, CDP, TCFD, CSRD, SBTi).

Strong analytical communicator capable of translating complex AI concepts for non-technical stakeholders.

Proactive mindset—comfortable taking initiative, pushing technical boundaries, and learning through rapid iteration.

Exceptional self-motivation and time management skills tailored for a remote-first work environment.

High proficiency in English (C1+).

Based in and eligible to work in the Netherlands, ideally Randstad.

Be part of a mission-driven company making a real, measurable climate impact.

Real-world experience building and shipping production-grade LLM architectures, agentic harnesses, and evals using modern tools like Langfuse and Supabase.

Hands-on autonomy and true feature ownership from day one—not just toy projects or research code.

Direct mentorship from experts across sustainability, modern AI/software engineering, and startup/scale-up strategy.

Access to state-of-the-art AI tooling, APIs, and frameworks to keep your technical stack cutting-edge.

Fast-track your career in a rapidly growing domain, setting you up for high-impact roles in climate tech and AI engineering.

Potential for full-time employment post-internship based on performance and business growth.

Competitive base compensation and paid vacation days.

Hybrid work setup: collaborate in-person at our shared office space in Rotterdam, with the flexibility to work remotely.

Work-from-home allowance and travel compensation included.

Vibrant culture with fun team outings and opportunities for international trips.