As a senior technology leader, you will help build our technology platform to enable 10 million change-makers to deliver a billion acts of goodness by 2025. We seek a platform-first Architect to lead enterprise patterns for reliable, governed, AI-driven, and cost-effective solutions at scale across our technology portfolio. You will design how data flows across the company, from ingestion to consumption, while ensuring our AI systems are secure, auditable, and maintainable. This role requires practical systems thinking and the ability to influence senior engineers and leadership toward consistent, enterprise-wide architecture outcomes that align our data and AI strategy with broader business goals.

If you're passionate about leveraging modern technology, data and AI for positive impact and eager to contribute to a mission-driven organization, we want to hear from you.

What you will do:

• Develop and maintain end-to-end tracks with our data and AI focus technology strategy and architectural portfolio
• Mentor engineers and technical leadership by providing clear patterns, ensuring adherence to architectural patterns, and offering hands-on guidance for complex implementations
• Lead architecture decisioning through Architecture Decision Records (ADRs), standards, and design reviews
• Oversee architectural reviews, code reviews, and system performance analysis to ensure quality standards and sustainable delivery momentum
• Foster a culture of collaboration, knowledge sharing, and continuous learning through mentorship, team collaboration, and workshops
• Enable governed data consumption through clear data contracts, curated datasets, and consistent serving patterns including domain marts
• Standardize end-to-end data flow patterns including ingestion, transformation, storage, serving, and retirement with repeatable templates
• Set platform standards for orchestration and reliability including SLAs, retries, idempotency, backfills, runbooks, and operational dashboards
• Establish enterprise data quality practices including critical data elements, quality rules, validation layers, monitoring, and issue triage workflows
• Drive governance-by-design by embedding metadata, lineage, classification, and ownership into platform patterns
• Drive adoption of AI governance architecture for agentic solutions including controls for data privacy and model lifecycle
• Define AIOps standards ensuring AI systems have traceability, quality measurement, incident response readiness, and cost guardrails
• Collaborate with stakeholders and product management to identify, prioritize, and mitigate technical risks and challenges
• Stay informed about industry regulations, security standards, and compliance requirements to ensure solutions meet necessary standards

What you’ll bring:

• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field
• 7+ years in software development methodologies, architecture, and implementation of large scale enterprise systems
• 4+ years focused on data engineering, data management, or data platform architecture and designing AI solutions including AIOps practices
• Structured problem solving to turn ambiguous requirements into scalable, low-cost solution patterns
• Ability to think strategically while paying close attention to technical details
• Proven experience building or evolving an enterprise data platform including standards and adoption across multiple teams
• Demonstrated ability to design governance-ready AI solutions including evaluation strategies, privacy safeguards, and auditability
• Strong expertise in system architecture, cloud computing, distributed systems, and integration technologies
• High bar for operational readiness, actionable documentation, and treating governance as a built-in platform feature
• Deep experience across modern data platform capabilities including AWS Glue, Step Functions, Airflow, dbt, Spark, and Snowflake
• Proficiency in programming and analytics using Python, SQL, and Jupyter Notebooks
• Experience with agentic frameworks such as LangChain, LlamaIndex, or LangGraph and AIOps tooling like LangFuse
• Familiarity with Agile development methodologies and the ability to adapt to a fast-paced environment
• Strong understanding of security principles, performance optimization, scalability, and reliability
• Demonstrated influence towards simplicity and repeatability in architecture

Nice to Have:

• Experience operating in regulated environments, (SOC2, ISO 27001, or GDPR).
• Familiarity with federated domain ownership models, where domains ship data products while the platform provides shared standards and tooling.
• Experience designing and scaling platform observability for data pipelines, streaming systems, and AI services.
• Familiarity with medallion architecture patterns
• Experience in modern data platform capabilities, including:
• Streaming: Apache Kafka, AWS MSK, AWS Kinesis, GCP Pub/Sub
• Metadata and governance: DataHub, Atlan or similar

What You'll Be Doing:

• Design and build scalable data pipelines, batch jobs, and streaming processes that power analytics and machine learning.
• Implement and optimize data storage systems (warehouses, lakes, analytical databases) with a focus on reliability, lineage, and governance.
• Develop tools and frameworks to support data orchestration, ETL workflows, and big data processing.
• Collaborate with engineers, data scientists, and product managers to align platform capabilities with business needs.
• Ensure data systems meet requirements for quality, scalability, and cost efficiency in cloud environments.
• Contribute to technical discussions, code reviews, and system design sessions.
• Take ownership of features and projects, driving them from concept to production.