AI Enterprise Engineer
Software Engineering, Data Science
Chicago, IL, USA
USD 150k-180k / year
Why Work at Lenovo
Description and Requirements
About Our Team
We are building Qira, Lenovo's next-generation cross-device Personal AI platform that delivers intelligent, context-aware experiences across Windows, Android, and the cloud. Our AI Enterprise Engineering team is extending Qira into an enterprise-ready platform adopted by business customers at scale.
Location: Chicago, IL (Hybrid, 3 days onsite, 2 days remote)
About the Role
As an AI Enterprise Engineer, you are a senior individual contributor who builds the backend services and integrations that extend Qira into an enterprise-ready platform. You take significant components from design to production with a high degree of autonomy, and you raise the technical bar for the engineers around you.
Working on cross-functional teams, you will design, implement, debug, and optimize the components that let enterprises adopt Qira securely and at scale, from identity and access to the administration portal, workflow automation, and unified knowledge retrieval. Depending on assignment, you may focus on the enterprise foundation, the core enterprise product, or the integrations connecting them.
What You’ll Do
Own the design and delivery of significant components or subsystems end to end, with minimal oversight.
Design, develop, and integrate backend services and features that extend Qira into an enterprise-ready platform.
Implement enterprise foundation capabilities: identity and access integration (SSO, SAML, OAuth, RBAC, MFA), audit logging, and data segmentation.
Build and extend the Enterprise Admin Console so IT administrators can configure identity, connectors, agents, policies, and usage in one place.
Build integrations that connect Qira to enterprise systems such as corporate identity providers, workflow automation platforms, and enterprise knowledge sources.
Contribute to enterprise deployment and portability work, including BYOC (AWS/Azure/GCP), infrastructure-as-code, and data-residency requirements.
Lead design and code reviews, set engineering patterns, and mentor other engineers on the team.
Make and document architecture decisions within your area, balancing speed with enterprise security and maintainability.
Debug complex, multi-layer workflows spanning application, service, and platform components; perform performance analysis and optimization.
Basic Qualifications
8+ years of hands-on software engineering experience building and shipping production backend, distributed, or platform systems.
Experience owning complex components end to end and deliver with autonomy.
Strong programming experience in one or more modern backend languages (e.g., TypeScript/Node.js, Python, Go, Java, or Rust).
Solid understanding of software fundamentals: APIs, services, data stores, concurrency, and cloud deployment.
Experience leading technical design and mentoring other engineers.
Bachelor’s degree in Engineering, Computer Science, or a related technical field, or equivalent experience.
Preferred Qualifications
Experience delivering software that meets enterprise security, compliance, and IT manageability requirements (audit logging, data segmentation, access controls).
Experience taking products through enterprise security reviews or certifications (SOC 2, HIPAA, ISO 27001).
Familiarity with enterprise identity and authentication standards (SSO, SAML 2.0, OAuth, RBAC, MFA) and tools such as WorkOS or Auth0.
Experience with AI/ML systems, LLM-based applications, or intelligent workflows.
Hands-on experience with the team’s core toolchain (Cursor, Linear, and GitHub) is highly preferred, along with fluency in AI-assisted development workflows.
Experience with cloud platforms, infrastructure-as-code, and multi-tenant or BYOC deployment models.
Prior experience as an early or founding engineer on a 0-to-1 product.
Master’s degree in Engineering or Computer Science.