LLM Application Engineer

About the role

ActAI builds proactive applications for people who are not used to complex prompting, starting with an agent-first mobile communication app. As an LLM Application Engineer you will build the intelligence layer behind ActAI's AI experiences, working at the intersection of LLMs, software engineering and product. You will own problems end-to-end, from understanding user needs to designing agentic workflows, integrating models and tools, building evaluation systems and improving AI behaviour in production.

Key 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 to improve model behaviour
• Build evaluation frameworks and datasets to measure AI quality, reliability and regressions
• Debug AI systems across the stack, from prompts and model behaviour to orchestration, backend services and product UX
• Optimise AI systems for quality, latency and cost
• Work 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

Required profile

• 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

Required skills

• 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