AI Engineer — Local SEO

We’re looking for an AI Engineer specializing in Local SEO to design, build, and deploy autonomous AI employees/agents that perform full-scope local search optimization tasks. You’ll create agent architectures, prompt/chain-of-thought flows, and integrations so the AI can audit local listings, generate optimized local content and schema, manage Google Business Profile (GBP) updates, build and clean citations, and report results with minimal human supervision. You’ll collaborate with SEO strategists, product, and engineering to define success metrics, monitoring, and safe-guards for agent actions. Responsibilities -Design and implement autonomous AI agents (single- and multi-agent flows) that execute Local SEO workflows end-to-end. -Build prompt engineering patterns, tool usage interfaces, and decision policies so agents can assess, decide, and act on local SEO tasks. -Implement integrations with APIs and platforms (GBP/Google My Business, citation sources, CMS, analytics, rank tracking, CRM) and safe, auditable action logs. -Automate citation building and cleanup workflows with validation and conflict resolution. -Automate local on-page optimization: generate localized title/meta, content blocks, structured data (LocalBusiness schema), and internal linking suggestions. -Create automated local audit agents that scan for NAP inconsistencies, duplicate listings, review signals, and technical crawl issues. -Develop monitoring, alerting, and human‑in‑the‑loop controls to prevent risky agent actions and ensure quality. -Measure agent performance with KPIs (local rankings, citation counts, visibility, GBP impressions/calls, manual review pass rate) and iterate on models and prompts. Qualifications -Strong background in ML/AI system design with production deployments of agents or pipelines. -Experience with prompt engineering, LLM orchestration platforms, or agent frameworks. -Practical knowledge of Local SEO practices: GBP, citations, NAP consistency, local schema, review management, and ranking signals. -Experience integrating with third-party APIs and building reliable automation (webhooks, REST, authentication). -Proficiency in Python and common ML/AI libraries and frameworks. -Good engineering practices: testing, observability, logging, and CI/CD. -Excellent communication and ability to work with non-technical SEO stakeholders.