LLM Application Engineer

Overview

About A1 There are over 5 billion users using basic applications today such email, notes, tasks that are not AI-native. Our mission is to build a proactive smart assistant for everyday users to bring intelligence to conversations, errands, organising and workflows, with minimal prompting. Our product focuses on achieving high reliability for long-running workflows, persistent context, and real-wor

What you'll do

• About A1 There are over 5 billion users using basic applications today such email, notes, tasks that are not AI-native.
• Our mission is to build a proactive smart assistant for everyday users to bring intelligence to conversations, errands, organising and workflows, with minimal prompting.
• Our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion.
• The system must handle multi-step reasoning, interact with external tools, and remain reliable despite non-deterministic model behavior.
• Our objective is to help users complete tasks daily enjoyable with over ~90%* reduced time.
• About the Role As an LLM Application Engineer, you will build the intelligence layer that powers A1's AI experiences.
• You will work at the intersection of LLMs, software engineering, and product - designing agent workflows, improving model behaviour, and turning AI capabilities into reliable user experiences.
• You will own problems end-to-end, from understanding user needs, designing Agentic workflows, integrating models and tools, building evaluation system and continuously improving AI behaviour in production.
• Focus Build and ship LLM-powered applications and AI agent workflows Design systems for reasoning, planning, memory, tool uuse and multi-step execution Build reliable orchestration pipelines that turn probabilistic model outputs into predictable, observable, and safe actions Integrate LLMs with APIs, databases, search, internal services, and external tools.
• Develop prompting, context engineering, structured outputs, tool-calling, and other techniques to improve model behaviour Build evaluation frameworks and datasets to measure AI quality, reliability, and regressions Debug AI systems across the entire stack-from model behaviour and prompts to orchestration, backend services, and product UX Optimise AI systems for quality, latency, and cost Work closely with product and engineering teams to turn ambiguous product problems into working AI solutions Establish production practices for observability, tracing, experimentation, evaluation, and continuous improvement Tech Stack Python LLM APIs and model providers, including OpenAI-compatible APIs and open-weight models Agent frameworks and orchestration systems Vector databases and retrieval systems Backend services, APIs, and distributed systems PyTorch / JAX Ideal Exper.

Requirements

• Practical experience with A1 Engineering.
• Relevant academic or project background for a LLM Application Engineer role.
• Strong written and verbal communication in English.
• Comfortable working on-site in Germany.

Skills