LLM Application Engineer
Bjak · Remote · United States ·
COMPENSATION
€•• – ••k
Listed on the employer's job board (Ashby)
- Fully remote
- LLM & Agent focus
- Python stack
- Production AI systems
- End-to-end ownership
You will work at the intersection of large language models, software engineering, and product design. Your primary focus is building systems for reasoning, planning, and memory that power ActAI's AI experiences.
The team aims to reduce hallucinations and ensure high reliability for long-running workflows. You will own problems end-to-end, from understanding user needs to improving AI behavior in production through systematic evaluation.
What you'll do
- Build and ship LLM-powered applications and AI agent workflows
- Design systems for reasoning, planning, memory, and tool use
- Create orchestration pipelines for predictable and safe actions
- Integrate LLMs with APIs, databases, search, and external tools
- Develop prompting and context engineering techniques to improve behavior
- Build evaluation frameworks to measure AI quality and reliability
- Debug AI systems across model behavior, prompts, and backend services
- Optimize AI systems for quality, latency, and cost efficiency
- Collaborate with product teams to solve ambiguous problems with AI
- Establish production practices for observability and continuous improvement
What you'll need
- Strong software engineering fundamentals and clean code practices
- Experience building AI-powered applications or agent-based systems
- Hands-on experience with LLMs and generative AI technologies
- Skill in designing prompts, workflows, and evaluation methods
- Ability to work across model, system, and product abstraction layers
- Strong problem-solving skills in fast-moving and ambiguous environments
- Bias toward shipping, iteration, and continuous improvement
Stack
- Python
- LLM APIs
- OpenAI-compatible APIs
- Open-weight models
- Agent frameworks
- Vector databases
- Retrieval systems
- Backend services
- Distributed systems
- PyTorch
- JAX