Application Solution Architect

Role Description

This is a remote position. Owning the end-to-end solution architecture of the Daitics AI CDP: a sovereign, on-prem, telco-native Customer Data Platform built on a streaming architecture, deployed on infrastructure we run ourselves (Kubernetes, Helm). The platform processes hundreds of thousands of events per second across thirty or more source systems and delivers unified customer profiles for B2C persons and B2B organizations, accounts, sites, lines, devices, and contacts. You will own the architecture across the five planes (Authoring, Control, Data, Activation, Observability) and the five layers (atomic events, tile primitives, trait values, signal filters, signal events), hold the line on architectural principles across engine boundaries, and translate them into designs engineering teams can build against.

Qualifications

• 12+ years in software and data engineering, with at least 5 years owning solution or platform architecture for large-scale distributed systems.
• Demonstrated ownership of end-to-end architecture for a streaming data platform on self-managed infrastructure (on-prem or private cloud).
• Deep, hands-on architectural command of Apache Flink as a stateful streaming runtime.
• Proven ability to design two-tier latency architectures.
• Experience designing Kafka topologies for multi-tenant platforms.
• Experience architecting schema governance across producers and consumers.
• Hands-on architecture experience with lakehouse table formats on S3-compatible object storage.
• Experience designing governed single-writer patterns.
• Experience with distributed in-memory caches.
• Ability to define and enforce a state-placement decision framework.
• Experience designing aggregation architectures that serve arbitrary rolling windows.
• Experience architecting identity resolution at scale.
• Experience modeling entity lifecycle state machines in streaming systems.
• Architecture experience with consent enforcement and data governance.
• Experience architecting tokenization, hashing, masking, and encryption for sensitive identifiers.
• Experience designing end-to-end lineage and edit-time impact analysis.
• Experience designing versioned artifact activation and cutover across engine boundaries.
• Ability to reason about state reconciliation when a computation definition changes.
• Experience designing multi-tenant isolation on Kubernetes.
• Experience architecting authentication, authorization, and network security.
• Experience defining failure domains, SLOs, RPO and RTO targets for streaming platforms.
• Ability to size a platform of this shape end to end.
• Judgement on when to wrap an open-source component behind a stable platform service interface.
• Experience with a canonical or industry semantic model.
• Experience integrating ML into a streaming platform.
• Practical experience with Spring Boot on Java for control-plane microservices.
• Experience with observability stacks.
• Familiarity with graph and vector substrates for lineage, relationship traversal, and semantic similarity over platform metadata.
• Ability to author and maintain a layered architecture corpus.
• Familiarity using AI tools for design, development, and debugging.

Requirements

• Experience with Apache Flink, Kafka, and distributed systems.
• Hands-on experience with lakehouse formats and in-memory caches.
• Expertise in data governance and consent enforcement.
• Strong understanding of multi-tenant architectures on Kubernetes.
• Experience with observability and monitoring tools.

Benefits

• Competitive salary.
• Flexible working hours.
• Remote work opportunities.
• Professional development and training.