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AI Interaction Designer

bright vision technologies·US·United States·mid
llm
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Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential. Job Title: AI Interaction Engineer Location: 100% Remote (U.S.) Position Type: Full-time, Direct W2 Salary Range: $100,000–$150,000 Annually Experience Required: 6+ years Sponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position. Job Summary: We are looking for a AI Interaction Engineer to define and lead the strategy, patterns, and tooling for designing prompts, agentic workflows, and LLM-based application architectures across the organization. The role combines deep practical mastery of modern LLMs with the discipline of building reusable design patterns, evaluation frameworks, and developer tooling that scale across many teams and use cases. The ideal candidate has shipped LLM-powered products in production, is fluent in prompt design patterns and agent architectures, and brings strong judgment about when and how to apply different LLM techniques responsibly. Key Responsibilities 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

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