Remote LLM Prompt Architect & Tooling Leader

Bright Vision Technologies; Wesley Chapel (FL); Remote; USD 100,000 - 150,000; Full time

Job summary

Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. We are seeking a Prompt Engineering Architect to define and lead the strategy, patterns, and tooling for designing prompts, agentic workflows, and LLM-based application architectures across the organization.

The ideal candidate ships LLM-powered products, masters prompt design patterns, and brings strong judgment on applying LLM

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Computational Linguistics, or a related field.
• Six or more years of software engineering experience, with significant time on LLM-based applications.
• Demonstrated experience shipping LLM-powered products to production.
• Deep familiarity with modern LLM APIs and agent frameworks.
• Strong understanding of retrieval-augmented generation, embeddings, and vector databases.
• Experience designing evaluation pipelines for non-deterministic systems.
• Strong Python skills and comfort with modern application frameworks.
• Solid grasp of responsible AI principles, including safety and policy considerations.
• Excellent written and verbal communication skills.
• Track record of mentoring engineers and influencing technical direction.

Skills

Python

LLM APIs

Agent frameworks

Communication skills

Mentoring

Education

Bachelor’s or Master’s degree in CS / related field

Tools

Vector databases

Embeddings

Job description

Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. We are seeking a Prompt Engineering Architect to define and lead the strategy, patterns, and tooling for designing prompts, agentic workflows, and LLM-based application architectures across the organization.

The ideal candidate ships LLM-powered products, masters prompt design patterns, and brings strong judgment on applying LLM