AI Engineer

• Design and Refine Prompts: Craft and optimize prompts for large language models and occasionally create agent flows to power end-to-end automation

• Integrate AI: Work closely with a Business Integration Engineer to embed LLMs into tools like Make or serverless functions. Ensure solutions are flexible, data-driven, easy to maintain, and can interact with our backend and internal toolsets

• Proactive Innovation: Actively analyze workflows involving complex or unstructured data to identify inefficiencies. Propose prompt-based improvements and AI-driven solutions—leveraging Retrieval-Augmented Generation (RAG) and vector search—to refine reasoning and decision-making

• Own Your Solutions: After onboarding, independently manage prompt-related projects, maintain quality, and quickly resolve production issues

• LLM Expertise: Proven skill in crafting effective prompts for large language models and experience with Retrieval Augmented Generation (RAG)

• Agent-Based Reasoning: Some experience with agent-based systems or a strong willingness to learn how to create autonomous agents that can plan, reason, and execute actions toward defined goals

• Data and Integration Familiarity: Comfortable with APIs, simple ETLs, and basic SQL. Able to connect LLM outputs to various systems without overcomplicating the process

• Development Knowledge: Familiarity with programming concepts and at least one high-level programming language (preferably Python)

• Pragmatic Engineering: Deliver practical solutions without over-engineering. Maintain a realistic understanding of state-of-the-art capabilities

• Fluent English

What We Offer:

A close-knit team where your impact is immediate and visible

A hybrid work model (3 days in-office, 2 days remote)

Support for professional growth through training and workshops

A results-driven culture free from unnecessary bureaucracy