Staff Engineer, Data and AI

Change.org is the world’s largest platform for democracy, empowering over 100 million people annually to create change. We are investing heavily in AI to build powerful tools that give people greater voice and foster shared solutions across the political spectrum. Our core petitions platform is being rebuilt from the ground up, and we will soon launch a new platform to identify common-ground issues and mobilize hundreds of millions of people to advocate for solutions.

About the role

As a Staff Engineer, Data and AI Enablement, you will build and scale the data and AI platform powering trusted insights, personalization, and AI-enabled experiences. Reporting to the Senior Director of Data Engineering, you’ll partner with teams across the organization to develop the platform, pipelines, architecture, and tooling that drive features, experimentation, and data-driven decision-making.

Key Outcomes

• Partner with PMs to translate business and product opportunities into scalable data and AI solutions, from exploration to production.
• Deliver reliable data products supporting AI-enabled features, experimentation, personalization, and decision-making.
• Build and scale batch and real-time pipelines for ingesting, transforming, and preparing high-quality data for reporting, ML training, model evaluation, and production inference.
• Evolve data and ML platform architecture using technologies like Airflow, Kafka, Redshift, Glue, Vector DBs, and cloud-native services.
• Improve data trust and usability through strong practices in data modeling, schema evolution, data contracts, testing, lineage, privacy controls, freshness, and recoverability.
• Enable teams to work independently by creating reusable tools, standards, and paved paths for data discovery and workflows.
• Maintain a resilient platform through observability, alerting, runbooks, incident response, on-call participation, performance tuning, and cost optimization.
• Raise the technical bar for data and AI infrastructure by leading architectural decisions, mentoring engineers, reviewing designs/code, reducing technical debt, and advancing AI and agentic workflows.

This role participates in an on-call rotation.

Core Competencies

• Distributed data systems expertise: Design and scale reliable batch and real-time data architectures.
• Strong software engineering judgment: Build maintainable, testable production systems in Python or comparable languages.
• Data modeling and SQL expertise: Design scalable, trustworthy data models and products.
• Cloud and platform architecture: Make sound trade-offs across compute, storage, orchestration, streaming, infrastructure, and cost.
• Operational excellence: Demonstrate ownership through observability, incident response, on-call participation, runbooks, performance tuning, and resilience.
• AI engineering fluency and technical leadership: Understand modern AI/LLM infrastructure and lead through architecture, collaboration, mentoring, and influence.

Requirements

• 7+ years of software engineering experience, with significant work in distributed systems, data platforms, ML platforms, or comparable production infrastructure.
• Hands-on experience building and operating large-scale batch and/or streaming data systems (e.g., Kafka, Spark, workflow orchestration).
• Experience designing and operating cloud-native data infrastructure (AWS/GCP, IaC, containers, orchestration, managed data services).
• Experience taking data or ML/AI systems into production, including reliability, observability, deployment, evaluation, and operational ownership.
• Practical experience with modern AI infrastructure (e.g., embeddings/vector retrieval, LLM evaluation, agentic workflows).

Location

This is a full-time role based in the United States, Canada, or Mexico. Eligible US locations: AK, AZ, CA, CO, CT, DC, FL, GA, IL, IA, KS, MD, MA, MI, MN, MO, NJ, NY, NC, OR, PA, RI, TX, VT, VA, WA, WI. Eligible Canadian locations: AB, BC, ON. Eligible Mexican locations: nationwide.

Pay

• United States: $236,000 (San Francisco, New York), $224,000 (Austin, Boston, Chicago, DC, LA, Seattle), $200,500 (all other US locations).
• Canada: $221,500 CAD (Vancouver, Toronto), $205,500 CAD (Victoria, Calgary), $202,000 CAD (all other Canadian locations).
• Mexico: $1,727,000 MXN (nationwide).

Benefits and perks vary by location.