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 model 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, reliability and regressions
• ▹Debug AI systems across the entire stack, from model behavior to orchestration and product UX
• ▹Optimize AI systems for quality, latency and cost
• ▹Work closely with product and engineering teams
• ▹Establish production practices for observability, tracing, experimentation and continuous improvement

Requirements

• ▹Strong software engineering fundamentals 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
• ▹Comfortable working across abstraction layers (model → system → product)
• ▹Strong problem-solving skills in ambiguous, fast-moving environments
• ▹Bias toward shipping, iteration and continuous improvement

Nice to have

• ▹Experience with Python, LLM APIs, agent frameworks, vector databases, PyTorch/JAX

Soft skills

About the company

A1's mission is to build a proactive smart assistant for everyday users, bringing intelligence to conversations, errands, organizing and workflows with minimal prompting, focused on high reliability for long-running workflows, persistent context and real-world task completion.