Principal Architect - DEX & AI

The role

DDN is looking for a hands-on principal architect who can set technical direction and build solutions across digital workplace, end-user computing, enterprise service management, and AI. This is a senior individual-contributor role, and the architect will write code, develop proofs of concept, build integrations, and help deliver agentic AI and other automation solutions into production. The role combines broad architecture ownership with practical engineering, sound security judgment, and close collaboration with platform teams.

What you’ll do

Architecture and hands-on engineering

• Develop and maintain reference architecture for Digital Employee Experience (DEX), spanning collaboration, endpoint services, identity dependencies, enterprise service management (ESM), automation and AI.

• Architect and help implement integrations across Google Workspace, Slack, Atlassian, ESM and endpoint platforms; resolve cross-platform design challenges with the engineering and security teams.

• Establish reusable patterns for identity, APIs, access, observability, integration and automation; maintain clear technical standards and architecture decisions.

• Contribute to endpoint and workplace technology standards and practical IT policies in partnership with the support, security, and procurement teams.

Agentic AI development and governance

• Personally design, build, and test agentic AI solutions, including enterprise knowledge retrieval, tool/API integrations, workflow orchestration, and approved actions; work with delivery teams to move useful solutions into production.

• Develop and troubleshoot agents, connectors, scripts and automation that work with Google Workspace, Slack, Atlassian, ESM and other approved business systems; deliver tested, documented and supportable code.

• Define and implement safeguards for agent permissions, data access, sensitive information, approval points, audit logging, and solution evaluation in partnership with Security, Legal, and service owners.

• Help select and implement Gemini Enterprise and other approved AI capabilities; assess technical feasibility, reliability, operating costs, and measurable employee benefit.

Delivery and technical leadership

• Stay directly involved in solution development beyond AI when needed, including proof-of-concept builds, APIs, custom integrations, workflow automation, and complex production troubleshooting.

• Review high-risk changes, major incidents, and recurring employee experience issues; diagnose root causes and help engineers implement durable fixes.

• Lead design and code reviews, mentor engineers, and explain technical trade-offs to IT leadership, while enabling platform teams to operate solutions long term.

What we’re looking for

• 10+ years in enterprise infrastructure, digital workplace, software/platform engineering or architecture, with evidence of both technical leadership and hands-on delivery.

• Strong coding and integration skills using Python, JavaScript/TypeScript or similar languages, REST APIs, authentication standards, and automation tools; comfortable testing and debugging solutions independently.

• Practical experience building AI-enabled applications, agentic workflows, or advanced automation; understanding of LLM APIs, knowledge retrieval, tool use, evaluation, and operational safeguards.

• Broad technical understanding of identity, SaaS collaboration, endpoint management, and ESM, including Google Workspace, Slack, Atlassian, and the integration patterns between them.

• Sound judgment about access controls, data protection, auditability, observability, software quality and service support in an enterprise environment.

• Ability to turn ambiguous needs into working solutions, lead cross-team design decisions and communicate trade-offs without relying on formal authority.

Helpful experience

• Delivery experience with Gemini Enterprise, Google Cloud AI services, enterprise search, or comparable agent development platforms.

• Familiarity with SOC 2/ISO 27001 controls and secure engineering practices such as source control, code review, CI/CD, and secrets management.

• Experience building scalable, reusable integrations and working with engineering and business teams in a growing global organization.

Initial priorities: Establish shared standards across workplace platforms and deliver practical agentic AI and automation solutions, with clear security controls, testing, and operational ownership.