What are the responsibilities and job description for the Senior System Architect position at Datavault AI Inc.?
Employment Type: Full-Time, Remote
About Us
Datavault AI, along with its event-technology subsidiary Event Citadel (formerly CompuSystems), operates across a diverse portfolio of technology and service divisions.
Datavault AI Inc. delivers high-performance computing software, Web 3.0 data-management solutions, and advanced audio technologies to a broad range of industries. Its Acoustic Science division licenses spatial and multichannel HD audio technologies—including ADIO®, WiSA®, and Sumerian®—to customers in sports & entertainment, events & venues, automotive, finance, and other sectors.
Event Citadel (formerly CompuSystems), founded in 1976, is a trusted provider of end-to-end event technology solutions, offering registration, ticketing, lead retrieval, and attendee-engagement services for events of all sizes across trade, association, corporate, and government markets.
Job Description
We are looking for a Senior System Architect with deep expertise in distributed systems, large‑scale data engineering, and advertising technology. You will architect the core data and systems foundation for a hybrid (on‑prem cloud) ad‑tech platform that supports real‑time decisioning, identity resolution, event processing, and cross‑channel activation.
This role requires hands‑on architectural leadership across high‑volume data pipelines, low‑latency services, and privacy‑aware data models. You will define the technical blueprint that enables deterministic and probabilistic identity, campaign orchestration, measurement, and analytics at scale.
Responsibilities
Systems Architecture
- Design distributed system architectures supporting sub‑100ms decisioning paths, high‑throughput ingestion, and horizontally scalable compute layers.
- Architect hybrid environments integrating on‑prem HPC clusters with cloud‑native services (AWS/Azure/GCP).
- Define service boundaries, API contracts, and data‑exchange protocols across the ad‑tech stack (e.g., OpenRTB, CAPI‑style event endpoints, identity sync interfaces).
- Build fault‑tolerant, autoscaling systems capable of handling billions of daily events.
Data Architecture & Engineering
- Design data models for identity graphs, event logs, attribution datasets, and campaign metadata.
- Architect multi‑tier storage systems (hot/warm/cold) using object storage, columnar warehouses, and in‑memory caches.
- Lead the design of real‑time and batch pipelines using technologies such as Kafka, Kinesis, Flink, Spark, Airflow, or dbt.
- Implement schema‑evolution strategies, data‑versioning, and lineage tracking across distributed systems.
- Optimize data flows for throughput, latency, and cost across hybrid compute environments.
Ad‑Tech Platform Foundations
- Architect systems supporting:
- Real‑time bidding and auction decisioning
- Audience segmentation and lookalike modeling
- Deterministic/probabilistic identity resolution
- Measurement, attribution, and incrementality workflows
- Consent and preference management
- Integrate with external ad‑tech systems (DSPs, SSPs, CDPs, clean rooms, identity providers).
- Implement privacy‑preserving data‑sharing patterns (hashed identifiers, differential privacy, clean room integrations).
Governance, Security & Compliance
- Define data governance frameworks including cataloging, lineage, retention, and access‑control models.
- Implement privacy‑by‑design principles aligned with GDPR, CCPA, IAB TCF, and event‑industry compliance requirements.
- Architect secure data‑exchange mechanisms using encryption, tokenization, and role‑based access controls.
Technical Leadership
- Provide architectural guidance to data engineering, platform engineering, and ML/analytics teams.
- Evaluate emerging technologies (PETs, vector databases, streaming engines, identity frameworks) and drive adoption where appropriate.
- Produce architecture diagrams, RFCs, and technical specifications for engineering teams.
Qualifications
- 5 years in system architecture, distributed systems engineering, or large‑scale data engineering.
- Strong expertise in:
- Distributed systems design
- SQL and NoSQL data modeling
- Event‑driven architectures
- Cloud platforms (AWS, Azure, or GCP)
- Hands‑on experience with:
- Data warehouses (Snowflake, Redshift, BigQuery)
- Streaming systems (Kafka, Kinesis, Pub/Sub)
- Orchestration frameworks (Airflow, Dagster, dbt)
- Deep understanding of data governance, security, and compliance frameworks.
- Strong ability to translate business requirements into scalable technical architectures.
Preferred (Ad‑Tech Focus)
- Experience building or integrating with DSPs, SSPs, CDPs, DMPs, or identity resolution systems.
- Familiarity with OpenRTB, VAST, CAPI‑style event ingestion, and auction mechanics.
- Experience with attribution modeling, MMM, MTA, or event‑level measurement systems.
- Knowledge of privacy‑enhancing technologies (clean rooms, differential privacy, secure multiparty computation).
- Experience with high‑volume log processing (10B events/day).
What We Offer
- Competitive compensation and benefits.
- Influence over the architectural direction of a next‑generation ad‑tech platform.
- Opportunities to work with high‑performance computing, Web 3.0 data systems, and advanced event‑technology infrastructure.
- A culture that values technical rigor, ownership, and innovation.