5 months ago
Responsibilities
- Define and socialize the end-to-end product and platform architecture strategy for a multi-tenant cloud-native SaaS data platform.
- Lead designs covering multi-tenant isolation, data models, schemas, indexing, OLAP, event-driven systems, APIs, service meshes, policy-as-code, and multi-cloud deployment.
- Drive reliability, security, privacy, and compliance practices including SLOs, error budgets, incident learning, threat modeling, encryption, secrets, key management, SBOM/SLSA controls, and chaos testing.
- Define production architecture patterns for RAG, agents, prompt and model governance, telemetry, evaluations, guardrails, and fallbacks.
- Improve developer experience through CI/CD, testing strategy, golden paths, paved roads, and reduced engineering toil.
- Mentor Staff and Principal engineers and architects, chair architecture reviews, and establish decision records, standards, and architecture radars.
- Communicate architecture options, risks, trade-offs, and business impact to executives, C-suite stakeholders, engineering teams, and enterprise customers.
- Translate customer requirements into pragmatic, phased designs while coordinating architecture and delivery across global teams and time zones.
Requirements
- 20+ years of experience in product or platform architecture for large-scale, cloud-native SaaS, including recent Principal or Distinguished Architect scope.
- Deep experience with Kubernetes and cloud platforms including EKS, AKS, GKE, AWS, Azure, and GCP, plus service meshes, observability, control planes, operators, CRDs, and golden paths.
- Expertise in high-volume streaming, low-latency queries, analytical and machine-learning workloads, batch and real-time processing, and data platforms.
- Experience with Kafka, Flink, Spark, Druid, ClickHouse, Cassandra, Elasticsearch or OpenSearch, API gateways, event-driven systems, and enterprise integration technologies.
- Experience with AI/ML production systems, ML pipelines, LLM and agent frameworks, RAG, tool use, memory, evaluations, and model governance.
- Strong knowledge of security, privacy, threat modeling, data classification, encryption and key management, and EU GDPR through real product work.
- Demonstrated executive communication, customer leadership, architecture evangelism, decision facilitation, and C-suite stakeholder influence.
- Proven ability to mentor senior engineers, establish documentation and review practices, and coordinate delivery across US, EU, and India time zones.
- Preferred experience owning multi-cloud platforms and data lake stacks, improving infrastructure cost and latency, and applying capacity planning, workload placement, and autoscaling.
- Programming fluency in Java, Scala, Python, Go, or Rust and contributions to relevant open-source frameworks are preferred.
Benefits
- Flexible work arrangements supported by Reltio’s distributed-workforce model.
- Equal employment opportunity workplace with reasonable accommodation for applicants with disabilities.
Tech Stack
Apache AirflowApache CassandraApache FlinkApache HadoopApache KafkaApache SparkAWSAzureClickHouseElasticsearchGoGoogle Cloud PlatformGrafanaIstioJavaKubernetesMLflowPrometheusPythonRustScala
About Reltio
Reltio builds a cloud-native master data management platform that unifies, cleanses, and governs customer and other core data for large enterprises. Delivered as a SaaS subscription, the Reltio Data Cloud consolidates data across sources in real time to support analytics, operations, and AI use cases in industries such as life sciences, financial services, and healthcare. Founded in 2011 and headquartered in Redwood Shores, CA, it operates as a subsidiary of SAP.