Staff Engineer, Data and AI

This is a fully remote position, open to applicants in United States, +28 more states.

📋 Description

• Collaborate with PMs to convert business and product opportunities into scalable data and AI solutions from initial exploration to production rollout.

• Provide dependable data products that support AI-driven features, experimentation, personalization, and organization-wide decision-making.

• Develop and scale batch and real-time pipelines for reporting, machine learning training, model evaluation, feature generation, and production inference.

• Enhance the architecture of data and ML platforms across orchestration, storage, compute, streaming, and data access.

• Increase data trust and usability through data modeling, schema evolution, data contracts, testing, lineage, privacy controls, freshness, and recoverability.

• Develop reusable tools, standards, and pathways that enable teams to discover data and create reliable workflows autonomously.

• Ensure platform resilience and efficiency through observability, alerting, runbooks, incident response, on-call participation, performance optimization, and cost management.

• Lead architectural decisions, mentor engineers, review designs and code, mitigate technical debt, and advance AI and agentic workflows.

• Participate in the on-call rotation.

• Report to the Senior Director of Data Engineering.

• Collaborate with teams across Change.org to build and scale the platform, pipelines, architecture, and tools that drive features, experimentation, and reliable decision-making.

⛳️ Requirements

• Over 7 years of software engineering experience with substantial experience in building distributed systems, data platforms, ML platforms, or similar production infrastructure.

• Hands-on experience in building and operating large-scale batch and/or streaming data systems.

• Familiarity with Kafka, Spark, workflow orchestration, or related technologies.

• Experience in designing and managing cloud-native data infrastructure using AWS/GCP, infrastructure as code, containers, orchestration, and managed data services.

• Proven track record of taking data or ML/AI systems into production, emphasizing reliability, observability, deployment, evaluation, and operational ownership.

• Practical knowledge of modern AI infrastructure, including embeddings/vector retrieval, LLM evaluation and observability, or agentic workflows.

• Capability to design and scale reliable batch and real-time data architectures.

• Strong software engineering judgment with the ability to create maintainable, testable production systems in Python and/or similar languages.

• Expertise in data modeling and SQL.

• Proficiency in cloud and platform architecture across compute, storage, orchestration, streaming, infrastructure, and cost.

• Operational ownership experience involving observability, incident response, on-call participation, runbooks, performance tuning, and resilient systems.

• Understanding of contemporary AI and LLM infrastructure.

• Provide technical leadership through architecture, collaboration, mentoring, and influence.

• Professional-level English proficiency is required.

• Resumes and application responses must be submitted in English.

• Must be legally authorized to work in the country where the position is located.

• Must indicate whether employment visa sponsorship is currently or eventually required.

🏝️ Benefits

• Benefits and perks vary by location.

• Equal opportunity employer.

• Reasonable accommodations available throughout the recruitment process.

• Support for professional-level English proficiency for all roles.