LLM Applications Engineer: Build Intelligent AI Workflows

Salt Digital Recruitment; United States; On-site; USD 120,000 - 180,000; Full time

Job summary

Salt Digital Recruitment seeks an LLM Application Engineer to bridge advanced model capabilities with production-ready products. You will design agent workflows, integrate models and tools, and continually improve AI behavior in a full-stack engineering role.

You will drive end-to-end implementations from requirements to deployment, focusing on reliability, latency, and cost while collaborating with product and engineering teams.

Qualifications

• Strong software engineering fundamentals with production applications.
• Hands-on experience developing LLM, Generative AI or agent-based systems.
• Experience building AI-powered apps beyond basic model integrations.
• Design prompts, agent workflows, evaluations and AI behaviour.
• Understanding of tool calling, context engineering, memory and multi-step agent execution.
• Ability to write clean, maintainable, production-ready code.

Responsibilities

• Build and ship LLM-powered applications and AI agent workflows.
• Design systems supporting reasoning, memory, tool use and multi-step execution.
• Build orchestration pipelines transforming model outputs into safe actions.
• Integrate LLMs with APIs, databases, search and internal/external tools.
• Develop prompting, context engineering and structured outputs for reliability.
• Create evaluation frameworks and datasets to measure AI quality and regressions.
• Debug AI systems across model behavior to product experience.

Skills

Software engineering fundamentals

LLM/Generative AI

Agent-based systems

Prompts and prompting

Agent workflows design

Evaluations and AI behaviour

Tool-calling and multi-step execution

Production-quality code

System-to-product translation

Tools

Python

LLM APIs

Vector databases

Retrieval systems / RAG

PyTorch

JAX

Backend services

Job description

Salt Digital Recruitment seeks an LLM Application Engineer to bridge advanced model capabilities with production-ready products. You will design agent workflows, integrate models and tools, and continually improve AI behavior in a full-stack engineering role.

You will drive end-to-end implementations from requirements to deployment, focusing on reliability, latency, and cost while collaborating with product and engineering teams.