Architect
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Key skills for this role
About the Role
Benevity seeks a platform-first Architect to lead enterprise patterns for reliable, governed, AI-driven solutions. You will design data flow from ingestion to consumption, ensure AI systems are secure and auditable, and mentor engineers.
Key Skills for This Role
Responsibilities
- 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
- 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
- Foster a culture of collaboration, knowledge sharing, and continuous learning
- Enable governed data consumption through clear data contracts, curated datasets, and consistent serving patterns
- Standardize end to end data flow patterns including ingestion, transformation, storage, serving, and retirement
- 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
Requirements
- Bachelor's or Master's degree in Computer Science, Software Engineering, or 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
- 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
- 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
Full Job Posting
Meet Benevity
- Benevity provides companies with technology to take social action through giving, volunteering, grantmaking, employee resource groups and micro actions.
- 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.
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
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
Nice To Have
- Experience operating in regulated environments (SOC2, ISO 27001, or GDPR)
- Familiarity with federated domain ownership models
- 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) and metadata/governance (DataHub, Atlan)
Where We Work
- At Benevity, we embrace a flexible hybrid approach to where we work.
- For those located near one of our offices, there’s no set requirement for in office time, but we value in person moments for connection and collaboration.
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