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About the Role

As an LLM Application Engineer, you will build the intelligence layer that powers AI experiences. You will work at the intersection of Large Language Models (LLMs), software engineering, and product designing agent workflows, improving model behavior, and turning Artificial Intelligence (AI) capabilities into reliable user experiences. You will own problems end-to-end, from understanding user needs, designing Agentic workflows, integrating models and tools, building evaluation systems and continuously improving AI behavior in production.

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 Large Language Models (LLMs) with APIs, databases, search, internal services, and external tools.
Develop prompting, context engineering, structured outputs, tool-calling, and other techniques to improve model behavior.
Build evaluation frameworks and datasets to measure AI quality, reliability, and regressions.
Debug AI systems across the entire stack from model behavior and prompts to orchestration, backend services, and product UX.
Optimize 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.

Requirements

Artificial Intelligence (AI) experience required.
Strong software engineering fundamentals with experience building AI-powered applications.
Hands-on experience with Large Language Models (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 from model to system to product.
Strong problem-solving skills in ambiguous, fast-moving environments.
Bias toward shipping, iteration, and continuous improvement.

Skills

Python
LLM APIs and model providers
OpenAI-compatible APIs
Open-weight models
Agent frameworks and orchestration systems
Vector databases and retrieval systems
Backend services
APIs
Distributed systems
PyTorch
JAX

Location

San Francisco, CA
Remote

Work Type

Work From Home
Remote

Salary/Compensations

USD 130000 - USD 175000 - yearly

Benefits

medical insurance
Dental
Vision
Savings Plan Options
PTO