Prompt Engineering Architect

Bright Vision Technologies

Prompt Engineering Architect designing LLM-based application architectures for innovative business solutions at Bright Vision Technologies. Leading strategies and tooling for prompt workflows and agentic systems.

Posted 5/17/2026full-timeRemote • New York • 🇺🇸 United StatesMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Define organization-wide standards, patterns, and reference architectures for LLM-based applications.
Design prompt structures, instruction templates, and retrieval strategies for diverse production use cases.
Architect agentic systems incorporating tool use, planning, memory, and multi-step reasoning.
Lead the design of retrieval-augmented generation pipelines including chunking, indexing, and reranking strategies.
Develop evaluation frameworks for prompt quality, agent reliability, and end-to-end task success.
Build internal tooling and libraries that accelerate LLM application development across teams.
Establish guardrails, safety filters, and policy enforcement patterns for LLM-powered products.
Collaborate with model engineering teams on prompt-model co-design and fine-tuning opportunities.
Conduct technical reviews of LLM application designs across multiple product teams.
Mentor engineers and applied scientists on prompt engineering and LLM application architecture.
Lead red-teaming exercises and continuously improve robustness against adversarial inputs.
Track latency, cost, and quality trade-offs in LLM application design and recommend optimizations.
Document patterns, anti-patterns, and lessons learned for broad internal reuse.
Stay current with LLM capabilities, tooling, and research, and translate advances into practical guidance.

Requirements

What you’ll need

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

Benefits

Comp & perks

Comprehensive benefits
Competitive compensation packages
Supportive work-life balance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

LLM-based applicationsprompt engineeringretrieval-augmented generationPythonevaluation pipelinesembeddingsvector databasesagent frameworksapplication frameworkssoftware engineering

Soft Skills

mentoringcommunicationinfluencing technical direction

Certifications

Bachelor’s degreeMaster’s degree