Solutions Architect at Lirio creating scalable cloud-native systems for behavioral science and AI applications while collaborating across functional teams.
Responsibilities
Architect scalable, secure, cloud-native solutions for Lirio’s agentic behavioral science and AI platform, including its distributed multi-cloud deployment architecture.
Translate business, clinical, behavioral science, and client requirements into clear architecture and integration designs.
Produce high-level and low-level design documents, including architecture diagrams, data and sequence flows, and technical specifications.
Ensure all solution designs align with Lirio’s platform strategy, architectural principles, and engineering standards.
Support both SaaS (Lirio-hosted) and customer-hosted deployments where the Lirio platform runs inside client cloud environments.
Contribute to architectural decision records (ADRs) and collaborate with the Architecture Team on platform evolution.
Design and guide integrations with key strategic platforms and ecosystems, including Microsoft Dynamics 365 and Azure Data & AI services.
Architect multi-channel engagement workflows across SMS, email, push, portal messaging, and other channels using providers such as Twilio, Mailgun, and similar services.
Contribute to the modernization and expansion of Lirio’s messaging and engagement capabilities, including replacement or consolidation of legacy vendor components.
Support event-driven and asynchronous architectures using technologies such as Kafka.
Requirements
10+ years experience designing distributed, cloud-native systems in SaaS or large-scale enterprise environments.
Bachelor's degree in related field.
Experience working closely with cross-functional technical and product teams.
Strong knowledge of software architecture and cloud platforms (AWS, Azure - preferred, OCI)
Proficiency with Kubernetes, containers, and cloud networking (VPC/VNet, private endpoints, hybrid connectivity).
Proficiency in programming languages such as Java, Python, or .NET.
Experience with event-driven architecture and messaging systems like Kafka.
Experience with relational and analytical data systems such as Postgres, Snowflake, and Databricks.
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