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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Staff Engineer, Data and AI - **Company:** Change.org - **Location:** San Francisco, CA, United States - **Experience:** Expert - **Salary:** $236,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Cloud Computing, Data as a Services, Data Security, Distributed Data Store, Distributed Systems, Python (Programming Language), Machine Learning, Performance Tuning, Cloud Services, Standard Sql, Azure Machine Learning, Software Engineering, Data Streaming, Workflow Management Systems, Privacy Controls, Large Language Models, Apache Spark, Model Validation, Technical Debt, Real Time Data, Apache Kafka, Data Management, Amazon Redshift - **Published:** August 16, 2026 - **Apply:** https://www.careerboard.com/us/en/find-jobs-in-United-States/-07A4E0893B23CA1EB0/ ## About the Role * 7+ years of software engineering experience, with significant experience building distributed systems, data platforms, ML platforms, or comparable production infrastructure. * Hands-on experience building and operating large-scale batch and/or streaming data systems, ideally including Kafka, Spark, workflow orchestration and similar technologies. * Experience designing and operating cloud-native data infrastructure using technologies such as AWS/GCP, infrastructure as code, containers, orchestration, and 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, such as embeddings/vector retrieval, LLM evaluation and observability, or agentic workflows. ## Description * 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. ## Related Videos - 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