LLM Application Engineer

United States · Remotefull timeRemote

H1B: no

Bjakcareer LLM Application Engineer at ActAI responsible for building the intelligence layer powering AI experiences. Designs agent workflows, improves model behavior, and integrates models and tools for reliable user experiences.

Responsibilities

As an LLM Application Engineer, you will build the intelligence layer that powers ActAI's AI experiences.
Build and ship LLM-powered applications and AI agent workflows
Design systems for reasoning, planning, memory, tool uuse 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, tool-calling, and other techniques to improve model behaviour
Build evaluation frameworks and datasets to measure AI quality, reliability, and regressions
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
Work closely 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
LLM APIs and model providers, including OpenAI-compatible APIs and open-weight models

Qualification

Hands-on experience with LLMsExperience designing promptsAbility to write cleanBias toward shipping

Required

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
Bias toward shipping, iteration, and continuous improvement