Principal Engineer, AI

Measured • Austin, TX

1d • Remote

About The Position

About Measured Measured is the pioneer and leader of incrementality-based media measurement and optimization. Since 2017, leading brands have used our AI-powered, all-in-one platform to manage, test, plan, and optimize over $35 billion in full-funnel media investments. Measured’s unique combination of automated experimentation, media mix modeling, and industry-leading expertise helps marketers prove the incremental impact of their advertising and maximize ROI with unmatched ease, accuracy, and efficiency. The Role We're looking for an AI Principal Engineer to lead and elevate the technical excellence of our AI/ML platform. In this strategic leadership role, you’ll be the driving force behind the design, implementation, and long-term architectural vision for our core AI infrastructure. You'll guide high-impact initiatives related to our core AI infrastructure, scalability, performance, foster a culture of engineering excellence in AI systems, and develop the next generation of technical leaders in this domain. As a technical visionary and seasoned leader, you'll work cross-functionally with engineering, data science, and product to shape the technical strategy and execution of our AI platform. You’ll provide architectural oversight for data pipelines, model serving, and training environments, establish MLOps best practices, and ensure our AI systems are built for reliability, maintainability, and massive scale. Your influence will extend across teams as you mentor senior engineers and managers, lead innovation efforts in AI infrastructure, and align technology decisions with business goals. Key Responsibilities Strategic Leadership & Technical Vision Drive the technical roadmap for AI/ML systems, aligning model development and deployment initiatives with key business outcomes. Establish and champion scalable AI delivery practices (evaluation, deployment, monitoring, governance) and production-grade architecture patterns and engineering standards. Identify and address strategic technical debt and performance bottlenecks within the core AI/ML platform and inference services. Lead the adoption of emerging AI research, foundational models, and deep learning frameworks that future-proof our platform's intelligence capabilities. Product AI and Agent Systems Build agentic workflows that can query metrics, run analyses, and cite supporting data Implement RAG patterns over internal schemas/data Establish an evaluation and guardrails framework: monitoring for drift/hallucinations, along with PII handling, tenant isolation, policy controls, and audit logging. Platform Engineering & Delivery Oversee production pipelines for AI services and ML workflows, including deployment, monitoring, and governance. Lead the development and evolution of scalable tools for prompt/agent versioning, experimentation, evaluation, release management, and monitoring. Ensure robust data validation, model testing practices, continuous integration/continuous delivery (CI/CD) for ML models, and automated deployment of AI services are in place. Promote engineering best practices for building explainable, ethical, and bias-aware AI systems through agile methodologies and continuous improvement. Organizational Development & Mentorship Build, mentor, and grow high-performing AI Engineering, Data Science, and AI Research teams and technical leaders. Partner with executive leadership to define and execute technical strategies for integrating AI across product lines and departments. Foster a culture of rigorous scientific experimentation, accountability in model performance, and cross-functional collaboration between research, data, and engineering. Serve as a senior technical advisor on complex AI/ML architectural decisions, providing guidance on model selection and influencing data product direction. Whatever else it takes to get the job done!

Requirements

• 10+ years of software engineering experience with a focus on modern technologies.
• 5+ years operating at a senior or principal engineering level, with demonstrated impact scaling teams, systems, and platforms.
• Strong experience building and operating production AI/ML systems, including model deployment and monitoring, and optimizing scalable, high-performance AI infrastructure.
• Hands-on experience building LLM-powered applications (e.g., OpenAI/Anthropic), including prompt/tool design, function calling, and RAG with vector databases
• Strong evaluation and production engineering background: LLM eval frameworks/experimentation, backend & distributed systems fundamentals, and strong SQL/warehouse fluency (Snowflake/Redshift/BigQuery)
• Strong background in component-based architecture, design systems, and performance.
• Technical proficiency in CI/CD, automated testing, Git workflows, and build systems.
• Familiarity with cloud platforms (AWS, GCP, or Azure), RESTful APIs, and GraphQL.
• Exceptional communication, decision-making, and problem-solving skills.
• A demonstrated ability to drive organizational change and technical innovation at scale.

Responsibilities

• Drive the technical roadmap for AI/ML systems, aligning model development and deployment initiatives with key business outcomes.
• Establish and champion scalable AI delivery practices (evaluation, deployment, monitoring, governance) and production-grade architecture patterns and engineering standards.
• Identify and address strategic technical debt and performance bottlenecks within the core AI/ML platform and inference services.
• Lead the adoption of emerging AI research, foundational models, and deep learning frameworks that future-proof our platform's intelligence capabilities.
• Build agentic workflows that can query metrics, run analyses, and cite supporting data
• Implement RAG patterns over internal schemas/data
• Establish an evaluation and guardrails framework: monitoring for drift/hallucinations, along with PII handling, tenant isolation, policy controls, and audit logging.
• Oversee production pipelines for AI services and ML workflows, including deployment, monitoring, and governance.
• Lead the development and evolution of scalable tools for prompt/agent versioning, experimentation, evaluation, release management, and monitoring.
• Ensure robust data validation, model testing practices, continuous integration/continuous delivery (CI/CD) for ML models, and automated deployment of AI services are in place.
• Promote engineering best practices for building explainable, ethical, and bias-aware AI systems through agile methodologies and continuous improvement.
• Build, mentor, and grow high-performing AI Engineering, Data Science, and AI Research teams and technical leaders.
• Partner with executive leadership to define and execute technical strategies for integrating AI across product lines and departments.
• Foster a culture of rigorous scientific experimentation, accountability in model performance, and cross-functional collaboration between research, data, and engineering.
• Serve as a senior technical advisor on complex AI/ML architectural decisions, providing guidance on model selection and influencing data product direction.

Benefits

• 100% Remote
• Total Rewards - Compelling compensation packages that include flexible time off, regional paid holidays, and regional health and wellness plans where available
• Social Engagement - virtual engagement, knowledge sharing, and more
• Giving Back - Opportunities to volunteer and impact our communities through Measured for Good initiatives
• Culture - Integrity, diversity, and award winning technology

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed