AI Software Engineer (m/w/d)

You'll work on cutting-edge projects involving text generation, semantic similarity search and agentic workflows. Responsibilities include evaluating LLMs, integrating them into our platform, orchestrating AI agents, and optimizing performance for scalability and efficiency. You'll work closely with software engineers and sustainability experts, leveraging your expertise to seamlessly integrate machine learning and AI powered capabilities into our software solution.

• Drive generative and agentic AI initiatives from ideation to deployment, ensuring solutions are robust, scalable, and seamlessly integrated into our platform.
• Work on generative and agentic AI, such as text generation with agentic RAG, semantic similarity, and classification, leveraging advanced models.
• Collaborate closely with software engineers to integrate GenAI and traditional ML models directly into our platform, focusing on efficiency, security, and performance at scale.
• Utilize modern LLMOps practices and TDD to ensure reliable, maintainable pipelines, ensuring models can be rapidly iterated and deployed.
• Partner with product management, sustainability experts, and the engineering team to translate business requirements into powerful AI-driven features that enhance our product’s capabilities and usability.

• Proficient in GenAI and Agentic workflows: Multiple years of hands-on experience in applied AI such as generative models (Gemini, Mistral, Claude, Llama or similar) in production, particularly for text-based tasks. Experience with Vertex AI is a huge plus.
• Programming and Model Integration Skills: Expertise in TypeScript and experience integrating language models into production systems with a focus on reliability, scalability, and security. Expertise in Python is a plus but not a must.
• Fullstack Development Skills: Skilled in building server-side components in TypeScript or Python. You understand the full spectrum of client-server architecture. Ideally, you have worked with frameworks like Angular and Nest.js before.
• LLMOps and CI/CD Experience: Knowledge of CI/CD practices, ideally with GitHub, to streamline and automate model development and deployment.
• SaaS Experience: You have worked on B2B SaaS applications and leveraged AI.
• Data Security and Performance Optimization: Strong understanding of security, data privacy, and performance tuning specific to machine learning and GenAI in cloud environments.
• GenAI Expertise: Proficiency in applying GenAI to enhance user experiences, with a good grasp of advanced text generation, summarization, and other generative tasks relevant to sustainability data processing.
• Collaborative and Quality-Driven: Values collaboration, engages in pair programming, and prioritizes high-quality work through peer code reviews.
• Initiative and Adaptability: Takes the lead on new projects, drives them to production, and continuously learns and improves based on outcomes.

We are a small, highly effective, and deeply product-minded team focused on delivering immediate value to sustainability teams. We believe in high autonomy, high responsibility, and building a foundation for scale.

• Technology Stack: Our backend uses Nest.js and Postgres, with a multi-tenant architecture. Our frontend is built with Angular as a Single Page Application (SPA). We use Nx for our monorepo.
• Development Culture: We are committed to daily shipping and leveraging automation wherever possible (CI/CD via GitHub). We prioritize code quality through peer reviews and dedicated testing practices (Testing Library, Testcontainers).
• Focus Areas: A key part of our work involves the development of our Proof AI (leveraging providers such as Gemini and Mistral) to make complex sustainability reporting effortless.

• Discovery Call with CTO 💻
• Live Coding Challenge with Engineer 💻
• Technical Interview with 1-2 Engineers 💻