LLM Application Engineer

Stack

Responsibilities

• ▹Build and ship LLM-powered applications and AI agent workflows
• ▹Design systems for reasoning, planning, memory, tool use and multi-step execution
• ▹Build reliable orchestration pipelines that turn probabilistic model outputs into predictable, safe actions
• ▹Integrate LLMs with APIs, databases, search, internal services and external tools
• ▹Develop prompting, context engineering, structured outputs and tool-calling techniques
• ▹Build evaluation frameworks and datasets to measure AI quality and regressions
• ▹Debug AI systems across the entire stack, from model behavior to backend services
• ▹Optimize AI systems for quality, latency and cost

Requirements

• ▹Strong software engineering fundamentals with experience building AI-powered applications
• ▹Hands-on experience with LLMs, generative AI or agent-based systems
• ▹Experience designing prompts, workflows, evaluations or AI behavior
• ▹Ability to write clean, production-quality code
• ▹Strong problem-solving skills in ambiguous, fast-moving environments

Nice to have

• ▹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 or JAX

Soft skills

About the company

A1 is building a proactive, AI-native assistant for everyday users that organizes communication, tasks and workflows with minimal prompting, aiming to significantly cut the time users spend on them.