Principal Software Architect

Job Summary

Sets data and applied AI architecture direction for OpenText, working across product lines rather than within a single team. Defines how OpenText builds and governs data platforms (warehousing, lakehouses, graphs, vector stores) and the applied AI systems built on top of them. Acts as a technical authority that other architects and engineering teams consult on data and applied AI decisions.

Responsibilities

• Design and review data architectures (warehouses, lakehouses, data platforms, graph and vector stores) that support analytics and AI workloads, including data quality, lineage, and governance (e.g., using layered patterns such as medallion/bronze-silver-gold where applicable).
• Evaluate and recommend data contract and product standards (e.g., ODCS, ODPS) for cross-product adoption.
• Define reference architectures and patterns for applied AI systems (RAG, agentic AI, LLM integration) that other product teams can adopt, including governance considerations such as safety filtering, bias assessment, human-in-the-loop mechanisms, and audit evidence requirements for autonomous/agentic systems.
• Advise on agentic AI architecture, including interoperability protocols such as MCP and A2A as well as emerging standards such as OpenID AuthZEN and OIDC-A.
• Partner with product architects across OpenText to align data and AI architecture decisions with company-wide standards.
• Represent data engineering and applied AI perspectives in architecture review boards and standards discussions.
• Communicate architectural trade-offs to executive and non-technical stakeholders, influencing direction across product lines without formal authority.
• Mentor other architects informally on data engineering and applied AI practices, without formal people-management responsibility.

Requirements

• 10+ years in software architecture, data engineering, or AI/ML systems, or equivalent demonstrated depth.
• Bachelors degree in Computer Science or equivalent professional experience.
• Track record operating as a software architect across multiple teams or products, not just within a single team.
• Demonstrated design of production data architectures at scale (e.g., data warehouse, lakehouse, or data platform), using layered patterns such as medallion/bronze-silver-gold where applicable.
• Hands-on experience architecting applied AI systems (e.g., RAG pipelines, LLM-integrated services) that have shipped to production.
• Experience building cloud-native applications on a major hyperscaler (AWS, Azure, or GCP), including containerized applications deployed on Kubernetes.

Qualifications

• Masters degree in Computer Science or a related field.
• Prior cross-product or cross-org architecture role at a similarly sized enterprise software company.
• Breadth across data warehousing, lakehouses, data platforms, graphs, and vector technologies, valued over deep specialization in a single area.
• Familiarity with data contract/product standards such as ODCS (Open Data Contract Standard) or ODPS (Open Data Product Specification).
• Familiarity with data catalog and metadata management tools (e.g., Unity Catalog, Google Cloud Dataplex Universal Catalog, Apache Atlas, or equivalent).
• Experience with graph databases and building knowledge graphs.
• Experience with vector database technologies and embedding pipelines in production RAG systems (e.g., pgvector, Milvus, or equivalent).
• Experience designing streaming data architectures (e.g., Kafka, Flink, Delta Live Tables, or equivalent) alongside batch/medallion patterns.
• Experience with agentic AI architecture and interoperability protocols (MCP, A2A) or similar emerging standards.
• Familiarity with agentic AI safety patterns, including prompt injection defenses, guardrail design, and PII handling in agentic contexts.

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