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 turning probabilistic outputs into predictable, observable, 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 stack: model behaviour, prompts, orchestration, backend, UX
• ▹Optimise AI systems for quality, latency and cost
• ▹Establish production practices for observability, tracing and experimentation

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 behaviour
• ▹Ability to write clean, production-quality code
• ▹Comfortable working across abstraction layers (model to system to product)
• ▹Strong problem-solving skills in ambiguous, fast-moving environments

Nice to have

• ▹Python, LLM APIs and model providers, including OpenAI-compatible and open-weight models
• ▹Agent frameworks and orchestration systems
• ▹Vector databases and retrieval systems
• ▹PyTorch / JAX

Soft skills

About the company

A1's mission is to build a proactive, intelligent assistant for everyday users (email, notes, tasks) that brings intelligence to workflows with minimal prompting, aiming to reduce time on tasks by ~90%.