LLM Application Engineer role building the intelligence layer powering AI experiences, from designing agentic workflows to model integration.
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, observable, and 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 reliability
- ▹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
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 → system → product)
- ▹Strong problem-solving skills in ambiguous, fast-moving environments
Nice to have
- ▹Python
- ▹OpenAI-compatible APIs and open-weight models
- ▹Agent frameworks and orchestration systems
- ▹Vector databases and retrieval systems
- ▹PyTorch/JAX
Soft skills
Problem-solvingIteration mindsetCross-functional collaborationOwnership
About the company
A1's mission is to build a proactive smart assistant for everyday users, focused on high reliability for long-running workflows, persistent context, and real-world task completion.
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