Semantic Retrieval / Vector Optimization Engineer

CiteWorks Studio; Northern (KY); Hybrid; USD 120,000 - 190,000; Full time

Job summary

CiteWorks Studio is seeking a Semantic Retrieval / Vector Optimization Engineer to design embedding pipelines and retrieval systems for enterprise-grade AI visibility products. You will map brand, page, entity, and competitor positioning in embedding space, translate vector distances into actionable recommendations, and partner with data science and product teams to ship dashboards.

The role emphasizes collaboration across engineering and analytics, with a focus on scalable, dashboard-driven AI

Qualifications

• Experience designing embedding pipelines and retrieval systems.
• Ability to translate vector metrics into product recommendations.
• Collaborative work with data science and product teams.

Responsibilities

• Design embedding pipelines that map brand, page, entity, and competitor positioning.
• Build retrieval systems that mirror how generative engines surface answers.
• Engineer cosine-gap analyses that translate vector distance into product recommendations.
• Partner with data science and product to ship intelligence into dashboards.

Skills

Embedding pipelines

Retrieval systems

Vector analytics

Dashboard integration

Cosine similarity analysis

Tools

Cosine similarity analysis

Job description

Semantic Retrieval / Vector Optimization Engineer

Engineering Remote · United States preferred

CiteWorks Studio is hiring a Semantic Retrieval / Vector Optimization Engineer to build the systems that analyze how brands, pages, entities, reviews, competitors, and authority signals sit in embedding space.

You will turn those insights into dashboard recommendations for AI visibility and generative engine optimization that enterprise teams can act on.

CiteWorks Studio is a full-service search visibility agency for enterprise brands and agency partners. We help brands improve where they rank, where they are cited, and where they are recommended by combining SEO auditing, AI search analysis, technical optimization, citation architecture, market intelligence, and in-house execution.

Our work is built around a simple market reality: buyers no longer discover brands through one channel. They move between Google, AI-generated answers, review pages, comparison articles, community discussions, videos, social platforms, and brand content before deciding who to trust.

CiteWorks Studio is moving toward a stronger SaaS and solutions model — turning agency intelligence, methodology, audits, dashboards, and corrective-action systems into scalable products.

About the role

Detailed responsibilities will be shared during the interview process. At a high level, you will:

• Design embedding pipelines that map brand, page, entity, and competitor positioning
• Build retrieval systems that mirror how generative engines surface answers
• Engineer cosine-gap analyses that translate vector distance into product recommendations
• Partner with data science and product to ship intelligence into dashboards