Solution Architect

• Own the target architecture and architecture decision records (ADRs).
• Finalize the durable workflow engine, tenancy model, and data-store boundaries within the first two weeks.
• Design and build the semantic resolution engine with AI engineers, translating plain-language definitions into systems, tools, and access rights.
• Define API contracts, event schemas, adapter contracts, supervisor graph state schemas, and security standards.
• Conduct design reviews, unblock engineers, and review critical code.
• Own scalability, tenant isolation, latency, data retention, disaster recovery, and load testing.
• Ensure the platform supports up to 10,000 concurrent runs.
• Collaborate with pilot customers' architects and security teams.

• Experience designing and shipping scalable, multi-tenant SaaS or platform products.
• Strong knowledge of distributed systems, durable workflows, sagas, Kafka, idempotency, back-pressure, and failure handling.
• Expertise in relational, in-memory, and vector databases.
• Production experience with LLM-based systems, tool calling, agent orchestration, LangGraph or equivalent frameworks, RAG, and evaluation.
• Enterprise integration experience with CRM, ERP, and legacy systems using REST, SOAP, JDBC, and file-based integrations.
• Strong understanding of B2B security architecture, RBAC, tenant isolation, secrets management, and PII handling.
• Hands-on coding experience and the ability to make and explain critical architecture decisions.

• Production experience with Temporal.
• Experience with Apache Camel or similar integration frameworks.
• Kubernetes operations at scale.
• Published technical talks, research papers, or open-source contributions.

• Multi-tenancy and enterprise security
• Distributed systems and durable workflow execution
• AI agents, semantic resolution, and RAG
• Enterprise integrations and data architecture
• Scalability, reliability, and disaster recovery

This hands-on Software Architect role shapes the architecture of a multi-tenant AI platform, spanning workflow execution, integrations, agent runtime, semantic resolution, and data stores. The work combines system design and implementation with engineering reviews, reliability and security standards, and collaboration with pilot customers.

Role at a glance

Skills mentioned

What you will likely work on

• Set platform architecture direction and document key decisions; establish the workflow engine, tenancy model, and data-store boundaries.
• Build semantic resolution capabilities with AI engineers, mapping plain-language definitions to systems, tools, and access rights.
• Define APIs, event and adapter contracts, agent supervisor state schemas, and security standards.
• Review designs and critical code, and help unblock engineering work.
• Address scalability, tenant isolation, latency, data retention, disaster recovery, and load testing, targeting up to 10,000 concurrent runs.
• Work with pilot customers’ architects and security teams on platform integration and security needs.

Good fit signals

• You have designed and shipped scalable, multi-tenant SaaS or platform products.
• You bring strong distributed-systems knowledge, including durable workflows, sagas, messaging, and failure handling.
• You have production experience with LLM systems, agent orchestration, retrieval-augmented generation, and evaluation.
• You can work hands-on in code and explain important architecture decisions while collaborating with engineers and customer technical teams.
• Experience with Temporal, integration frameworks such as Apache Camel, or Kubernetes operations at scale is advantageous.