Staff Engineer, Data and AI

Change.org http://Change.org is searching for a Staff Engineer, Data and AI Enablement to build and scale the data and AI platform behind Change.org http://Change.org powering trusted insights, personalization, and AI-enabled experiences that drive greater impact for millions of people creating change). You will report to our Senior Director of Data Engineering. As a key member of our Data and AI Enablement team, you’ll partner with teams across the organization to build and scale the platform, pipelines, architecture, and tooling that powers features, experimentation, and trusted decision-making. Change.org http://Change.org is the world’s largest platform for democracy. At a time when dissatisfaction with democracy globally is at an all-time high, we’re investing heavily in using AI to build an operating system for modern democracy. This includes our platform for giving people greater voice, a personalized voter guide for elections, and a new product which aims to bring people across the political spectrum together to identify shared solutions. To realize this vision, we're building a team at the intersection of technology and civic engagement — bringing together top talent focused on giving citizens a direct voice, strengthening accountability, and building stronger, more resilient democracies.. Key Outcomes: - Partner with PMs to translate business and product opportunities and our shared strategic vision into scalable data and AI solutions, from early exploration through production rollout. - Deliver reliable data products that support data and AI enabled features, experimentation, personalization and decision-making across the company. - Build and scale batch and real-time pipelines that ingest, transform, and prepare high-quality data for reporting, machine learning training, model evaluation, feature generation, and production inference. - Evolve the data and ML platform architecture across orchestration, storage, compute, streaming, and data access, using technologies such as Airflow, Kafka, Redshift, Glue, Vector DBs and other cloud native services. - Improve data trust and usability by establishing strong practices for data modeling, schema evolution, data contracts, testing, lineage, privacy controls, freshness, and recoverability. - Enable teams to work more independently by creating reusable tools, standards, and paved paths that make it easier to discover data and build dependable workflows. - Maintain a resilient and efficient platform through observability, alerting, runbooks, incident response, on-call participation, performance tuning, and ongoing cost optimization. - Raise the technical bar for data and AI infrastructure by leading architectural decisions, mentoring engineers, reviewing designs and code, reducing technical debt, and advancing the use of AI and agentic workflows. - This job is expected to participate in our on call rotation The most important core competencies for the role are: - Distributed data systems expertise: Able to design and scale reliable batch and real-time data architectures. - Strong software engineering judgment: Builds maintainable, testable production systems in Python and/or comparable languages. - Data modeling and SQL expertise: Designs scalable, trustworthy data models and data products. - Cloud and platform architecture: Makes sound trade-offs across compute, storage, orchestration, streaming, infrastructure, and cost. - Operational excellence: Demonstrates strong operational ownership through observability, incident response, on-call participation, runbooks, performance tuning, and building resilient systems. - AI engineering fluency and technical leadership: Understands modern AI and LLM infrastructure and leads through architecture, collaboration, mentoring, and influence. Target experience: - 7+ years of software engineering experience, with significant experience building distributed systems, data platforms, ML platforms, or comparable production infrastructure. -…