GT LLM Application Engineer, Artificial Intelligence (AI) Required, Work From Home Ginas Tech Jobs · Remote · US · AI Engineering $130,000–$175,000 12d ago

Aimlroles; San Francisco (CA); Remote; USD 140,000 - 210,000; Full time

Benefits offered by this job

Medical Insurance

Dental Insurance

Vision Insurance

Savings Plan

PTO

Job summary

Aimlroles seeks an LLM Application Engineer to build the intelligence layer powering AI experiences. You will work at the intersection of Large Language Models, software engineering, and product design, turning AI capabilities into reliable user experiences.

This position is 100% Remote. Responsibilities include shipping LLM-powered apps, integrating models with APIs and databases, designing prompts and evaluation systems, and ensuring observable, scalable AI workflows.

Qualifications

• AI experience in production systems.
• Strong software engineering fundamentals.
• Hands-on with LLMs or agent-based systems.
• Experience designing prompts and workflows.
• Ability to write clean, production-ready code.
• Comfort across model-to-product abstraction layers.

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 turning model outputs into safe actions.
• Integrate LLMs with APIs, databases, search, internal services, and external tools.
• Develop prompting, context engineering, structured outputs, tool-calling, and other techniques.
• Build evaluation frameworks and datasets to measure AI quality, reliability, and regressions.
• Debug AI systems across the stack—from model behavior to product UX.
• Optimize AI systems for quality, latency, and cost.
• Work closely with product and engineering teams to turn problems into AI solutions.
• Establish production practices for observability and experimentation.

Skills

AI experience

Software engineering fundamentals

LLMs / generative AI

Prompt design / workflows

Production-grade code

System design

Tools

Python

OpenAI-compatible APIs

Agent frameworks

Vector databases

PyTorch / JAX

Distributed systems

Job description

LLM Application Engineer, Artificial Intelligence (AI) Required, Work From Home

As an LLM Application Engineer, you will build the intelligence layer that powers the 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. This position is 100% Remote.

LLM Application Engineer 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.

LLM Application Engineer Outcomes

• Artificial Intelligence (AI) features reach production quickly and deliver measurable user impact.
• LLM-powered workflows are reliable, scalable, observable, and maintainable.
• Artificial Intelligence (AI) quality improves through systematic evaluation, experimentation, and iteration.
• Artificial Intelligence (AI) workflows become increasingly predictable, efficient, and cost-effective.
• Complex AI capabilities are translated into simple, intuitive user experiences.

LLM Application Engineer Qualifications

• 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.
• Tech Stack: 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, and PyTorch / JAX.

Benefits include medical insurance, Dental, Vision, Savings Plan Options, PTO, etc.

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