Senior Search Data and Systems Engineer, Organic and Agentic Search

Autodesk•San Francisco, CO

1d•$102,000 - $182,710

About The Position

We’re seeking a Senior Search Systems Engineer to build the intelligence and automation layer that sits on top of our marketing and AI visibility data. This role focuses on transforming structured data—produced by our data engineering and analytics systems—into decision frameworks, automated insights, and applied AI workflows that improve how our brand performs in AI-driven discovery environments. This role serves as the bridge between SEO and AEO strategy, analytics, and technical data implementation—helping define how search and AI visibility data should be collected, transformed, structured, monitored, and operationalized across Autodesk’s marketing ecosystem. While partnered closely with data engineering and BI teams, this role is responsible for ensuring the underlying datasets, instrumentation, custom dimensions, transformation logic, and reporting outputs accurately support SEO, AI visibility analysis, automation workflows, and decision-making systems at scale.

Requirements

7+ years of experience in software engineering, applied analytics, search systems, or technical marketing roles that required designing and owning complex systems end-to-end
Experience partnering with data engineering or analytics engineering teams to define transformation logic, data models, instrumentation requirements, and reporting outputs
Strong understanding of marketing and analytics data architecture, including event-level data, custom dimensions, warehouse modeling, and reporting layer design
Experience working with APIs, structured datasets, and large-scale analytical environments such as Snowflake, BigQuery, or similar cloud data platforms
Strong proficiency in Python, SQL, or similar languages, with an emphasis on building durable systems, not one-off analyses or prototypes
Experience designing analytical or decision systems that sit downstream of a data warehouse, including defining business logic, evaluation frameworks, and failure modes
Deep familiarity with search, discovery, or ranking systems (traditional or AI-driven), and the ability to reason about probabilistic outputs, model variance, and imperfect signals
Hands-on experience evaluating, prototyping, or productionizing AI-driven workflows, LLM-based systems, or agent-like architectures, with a pragmatic approach to risk and complexity
Ability to bridge technical implementation and business strategy by translating analytical needs into scalable data and systems requirements
Demonstrated experience operating in ambiguous problem spaces, where requirements were incomplete, tooling was immature, and success depended on judgment rather than predefined best practices
Proven ability to influence cross-functional partners by explaining technical tradeoffs clearly and pushing back when solutions are premature, fragile, or misaligned
Track record of documenting systems, assumptions, and decisions to support long-term maintainability and team learning
Comfort being the first or only person in a role, and helping define what “good” looks like before metrics or playbooks exist

Responsibilities

Define the data, instrumentation, and custom dimensions required to support SEO, AI visibility, content performance, and entity-level analysis across Autodesk’s marketing ecosystem
Partner with SQL developers, analytics engineers, and BI teams to operationalize scalable datasets, transformation logic, reporting tables, and analytical data models that support downstream reporting, automation, and decision systems
Shape ingestion and normalization strategies for search, behavioral, content, and AI visibility datasets across APIs, warehouses, and marketing platforms
Ensure data quality, consistency, and governance across SEO and AI visibility reporting systems by validating metric definitions, transformation logic, and analytical outputs
Translate ambiguous business questions and SEO hypotheses into structured technical requirements that can be implemented across reporting pipelines, analytical systems, and automation workflows
Define analytical frameworks and scoring logic for evaluating brand visibility, entity coverage, content performance, and competitive presence across traditional and AI-driven search environments
Develop monitoring and alerting systems that identify meaningful shifts in search visibility, AI model behavior, response patterns, or competitive movement over time
Build and maintain automation, prioritization models, and agent-like systems that transform curated datasets into actionable recommendations for SEO, content, and discovery optimization
Translate marketing strategies and initiatives into scalable technical implementations, including rule-based systems, experimentation frameworks, and applied AI workflows
Prototype and evaluate emerging tools, APIs, and frameworks related to LLM analysis, AI agents, search intelligence, and marketing automation
Partner with search, content, analytics, engineering, and platform teams to ensure search intelligence systems and AI-driven insights are embedded into planning, prioritization, experimentation, and execution workflows
Document system logic, assumptions, frameworks, and operational processes to ensure long-term scalability, maintainability, and organizational clarity