A

Appnovation

Develops and operates enterprise AI products

Senior Solutions Architect

Technology & Systems ConsultingPosted on Nov 11
Full-timeNo salary listedIn-person

About the Job

Requirements

  • A bachelor's degree in Computer Science, Engineering, Information Systems, or a related field, and 10+ years of technology experience, including significant experience in solution, enterprise, or data architecture.
  • Demonstrated experience designing cross-cloud and multi-cloud data architectures as a senior solutions or enterprise architect.
  • Proven application of zero-copy, data-mesh, and data-product principles, including domain-driven design.
  • Deep expertise in data governance, including attribute- and role-based access control, data sensitivity and policy classification, and geolocation-based access requirements.
  • Experience defining data-contract standards, such as the Linux Foundation Open Data Contract Standard, and embedding governance metadata into platform workflows.
  • A strong background in identity and access management for users and machine/agent identities, including OAuth/OIDC and service accounts.
  • Strong communication, stakeholder-management, and documentation skills, including the ability to explain complex technical trade-offs to technical and non-technical audiences.
  • Prior experience in a consulting or client-facing delivery environment, working across multiple concurrent initiatives and priorities.
  • Technical experience with Databricks and Snowflake; AWS-native data experience is a plus.
  • Technical experience with Collibra, Unity Catalog, Horizon, Neo4j, and knowledge graphs.
  • Technical experience with MCP, Snowflake Cortex and Genie, vector search, and embeddings.
  • Technical experience with Apache Iceberg and open table formats, YAML-based data contracts, Python, OAuth/OIDC and identity providers, and infrastructure-as-code such as Terraform.

Responsibilities

  • Own the end-to-end solution architecture for a governed, zero-copy data platform in which data remains in its source systems, working across Databricks, Snowflake, and adjacent cloud data sources.
  • Produce architecture artifacts, including decision records, reference architectures, and solution diagrams; establish design standards for the engineering team; and provide build-versus-integrate recommendations.
  • Define and prioritize catalog and metadata integration patterns across cloud and lakehouse environments.
  • Design agent- and MCP-based access patterns that expose governed data products to enterprise AI tools and agent platforms.
  • Establish future-state direction for data products, cross-source data composition, and agentic consumption, translating the evolving product vision into concrete design specifications.
  • Ensure alignment with the organization's enterprise engineering practices while guiding the engineering team toward agent-based data consumption.
  • Connect business priorities, enterprise architecture standards, and emerging technology into a practical target architecture that guides design and investment.
  • Communicate with engineering teams and senior stakeholders, frame build-versus-integrate trade-offs, build alignment, and drive decisions without relying solely on formal authority.
  • Guide engineers, challenge assumptions, evaluate emerging technologies, and make platform-scale technology choices.
  • Embed data governance, access control, and data-contract standards into platform workflows while balancing governed data-product openness with security, privacy, and compliance.
  • Transform evolving product vision and business requirements into technical designs and specifications for software developers, data engineers, and other technology stakeholders.
  • Explain technical solutions to technical and non-technical audiences and connect technology solutions with measurable business value.
  • Set standards for architecture quality, governance, performance, scalability, and security, and pursue continuous improvement.
  • Manage multiple initiatives and priorities and build internal and external client relationships.

Desired Qualifications

  • Familiarity with semantic layers, ontologies, knowledge graphs, and retrieval-augmented generation or vector search for data discovery.
  • Awareness of cross-cloud cost management and FinOps practices.
  • Experience operating in a regulated life-sciences or comparable compliance-driven environment, including GxP, GDPR/HIPAA, and PII/PHI handling.
  • AWS-native data experience.
  • Prior experience and connections in the life sciences industry.

About the Company

Appnovation

Develops and operates enterprise AI products

Appnovation designs, builds, and runs AI products for large enterprises using open-source models. Its main offering, AI product development, embeds forward-deployed engineers to create AI-native products and data assets like AI sales assistants or clinical tools. The Evolv e platform hosts and governs open models in the client’s cloud, routing workloads to the best model to avoid per-token fees and vendor lock-in while protecting IP and data. Beyond AI, it provides digital services in strategy, design, data, and engineering (including Drupal) for regulated industries like healthcare and insurance, aiming to help global brands deploy AI at scale.

Company size
201-500
Company stage
Late Stage VC
Total funding
$21.3M
Headquarters
Vancouver, Canada
Founded
2007

Recently Posted Jobs

Explore more opportunities at Appnovation

See more jobs