Remote AI Interaction Engineer — LLM Design & Tooling

Bright Vision Technologies; Chesterfield (MO); Remote; USD 140,000 - 155,000; Full time

Job summary

Bright Vision Technologies is seeking an AI Interaction Engineer to define and lead the strategy for prompts, agentic workflows, and LLM-based architectures across the organization. The role combines hands-on development with scalable patterns, evaluation frameworks, and tooling to enable multiple teams to build robust AI-powered solutions.

The ideal candidate has shipped LLM-powered products in production, is fluent in prompt design patterns and agent architectures, and understands responsible

Qualifications

• 6+ years of software engineering experience with LLM-based applications.
• Experience shipping LLM-powered products to production.
• Strong Python skills and comfort with modern application frameworks.
• Deep familiarity with retrieval-augmented generation, embeddings, and vector databases.

Responsibilities

• Define and lead strategy, patterns, and tooling for prompts and LLM architectures.
• Design prompts, agent workflows, and scalable developer tooling.
• Lead evaluation pipelines for non-deterministic systems.
• Mentor engineers and influence technical direction across teams.
• Collaborate on enterprise software integrations with compliance in mind.
• Communicate effectively with technical and non-technical stakeholders.

Skills

LLM development

Prompt design

Agent architectures

Evaluation pipelines

Python

Mentoring engineers

Communication

Responsible AI

Tools

LLM APIs

Vector databases

Python frameworks

Agent frameworks

Job description

Bright Vision Technologies is seeking an AI Interaction Engineer to define and lead the strategy for prompts, agentic workflows, and LLM-based architectures across the organization. The role combines hands-on development with scalable patterns, evaluation frameworks, and tooling to enable multiple teams to build robust AI-powered solutions.

The ideal candidate has shipped LLM-powered products in production, is fluent in prompt design patterns and agent architectures, and understands responsible