AI Enterprise Engineer

Key Responsibilities

• Design, develop, and deliver scalable backend services and enterprise platform capabilities.

• Own significant components and subsystems throughout the software development lifecycle with minimal oversight.

• Build and extend enterprise-grade AI platform services and integrations.

• Develop and implement enterprise security capabilities, including:

  • Single Sign-On (SSO)

  • SAML 2.0

  • OAuth

  • Role-Based Access Control (RBAC)

  • Multi-Factor Authentication (MFA)

  • Audit Logging

  • Data Segmentation and Access Controls

• Build and enhance enterprise administration capabilities that enable administrators to manage identities, connectors, policies, agents, and platform configurations.

• Develop integrations with enterprise systems, including:

  • Corporate Identity Providers

  • Workflow Automation Platforms

  • Enterprise Knowledge Management Systems

• Design and implement cloud-native solutions across AWS, Azure, and Google Cloud Platform environments.

• Contribute to multi-tenant and Bring Your Own Cloud (BYOC) deployment models while ensuring compliance with data residency requirements.

• Perform architecture design, code reviews, performance optimization, and technical mentoring.

• Debug and optimize complex, multi-layered workflows spanning applications, services, and cloud platforms.

• Make and document architectural decisions while balancing scalability, maintainability, security, and delivery timelines.

• Champion engineering best practices and establish technical standards across teams.

Required Qualifications

• 10+ years of hands-on software engineering experience building and delivering production-grade backend, distributed, or platform systems.

• Demonstrated experience owning complex technical components end-to-end with minimal supervision.

• Strong programming expertise in one or more of the following:

  • TypeScript / Node.js

  • Python

  • Java

  • Go

  • Rust

• Strong understanding of:

  • APIs and Microservices

  • Distributed Systems

  • Data Stores and Database Technologies

  • Concurrency and Performance Optimization

  • Cloud-native Architectures and Deployments

• Experience leading technical designs, conducting code reviews, and mentoring engineers.

• Bachelor''s degree in Computer Science, Engineering, or a related technical discipline (or equivalent practical experience).

• Experience building enterprise software that meets security, compliance, and IT manageability requirements.

• Experience with enterprise security certifications and compliance frameworks such as:

  • SOC 2

  • HIPAA

  • ISO 27001

• Strong understanding of enterprise identity and authentication technologies, including:

  • SSO

  • SAML 2.0

  • OAuth

  • RBAC

  • MFA

  • Identity management platforms such as WorkOS or Auth0

• Hands-on experience building:

  • AI/ML Systems

  • Large Language Model (LLM)-based Applications

  • Intelligent Workflow Automation Solutions

• Experience working with AI-assisted development environments and modern engineering toolchains.

• Experience with:

  • Infrastructure-as-Code (IaC)

  • Multi-tenant Platform Architectures

  • Cloud Deployment Models

  • Bring Your Own Cloud (BYOC) Implementations

• Prior experience working as an early-stage or founding engineer building 0-to-1 products is highly desirable.

• Master''s degree in Computer Science, Engineering, or a related technical field is preferred.