About The Position
We are looking for a proactive Staff IT Engineer to lead technical enablement for Openlyʼs AI adoption program. This role will help accelerate enterprise-wide AI usage by building practical automations, integrating AI tools with internal systems, and turning high-value business problems into reliable internal solutions. This person will sit at the intersection of IT, security, infrastructure, and platform engineering. The role will own and improve the technical foundations for AI enablement, including tool rollout, integration patterns, MCP connectivity, workflow automation, and the operational standards required to scale adoption safely. The right candidate will be hands-on, product-minded, and able to move from rapid prototype to supportable internal solution.
Requirements
- Bachelorʼs degree in Information Technology, Computer Science, Engineering, or a related field, or equivalent practical experience.
- 8+ years of experience in IT engineering, systems engineering, platform engineering, automation, DevOps, or a closely related role.
- Strong experience designing and delivering internal tools, automations, or platform capabilities from idea through production.
- Strong understanding of AI-enabled workflows, prompt-driven systems, agent patterns, and practical business applications of modern AI tools.
- Experience integrating enterprise systems, knowledge sources, and APIs into useful internal workflows or automations.
- Experience building and maintaining API-driven services, scripts, and automations using Python, JavaScript, Bash, or similar languages.
- Experience with Terraform or similar infrastructure-as-code frameworks.
- Experience with GitHub, Git, and modern software delivery practices.
- Strong knowledge of cloud infrastructure such as GCP or AWS.
- Familiarity with identity and access patterns such as OAuth2, OIDC, SAML, or equivalent enterprise authentication mechanisms.
- Ability to design context-aware workflows that maintain continuity across tools and systems, including thoughtful use of MCP and related integration patterns.
- Ability to troubleshoot complex issues across SaaS systems, integrations, automation layers, and cloud infrastructure.
- Product thinking: Identifies high-value problems, evaluates solution options carefully, and focuses effort where AI and automation can create meaningful business impact.
- Strategic thinking: Connects immediate technical work to broader architectural goals and organizational priorities.
- Effective communication: Explains technical concepts clearly, facilitates crossfunctional collaboration, and creates documentation that others can use.
- Innovation: Finds opportunities to simplify processes, reduce SaaS dependency, and improve employee productivity through better tooling and automation.
- Dealing with ambiguity: Operates effectively in fast-moving, uncertain environments and can define structure where little exists.
- Architecture: Designs systems and workflows that are scalable, secure, and maintainable over time.
- Mentorship: Shares best practices openly, supports the growth of others, and raises the technical standard of the team.
Nice To Haves
- Experience supporting enterprise rollout and enablement of AI tools such as Claude, Copilot, or similar platforms.
- Experience with retrieval, knowledge integration, or context management patterns for AI-enabled workflows.
- Familiarity with multi-step agent workflows and orchestration patterns.
- Interest in AI governance, security, and responsible-use frameworks.
- Ability to deliver fast prototypes without losing sight of reliability, supportability, and enterprise standards.
Responsibilities
- AI solution development: Build and deploy AI-enabled tools, workflows, and internal automations that improve productivity and reduce repetitive work across the company.
- Integration and enablement: Connect AI agents, tools, and automations with enterprise systems such as Okta, Google Workspace, Slack, Notion, Jira, and other applications, ensuring reliable interoperability.
- MCP and platform ownership: Build, maintain, and improve MCP connections and supporting infrastructure, including standards for configuration, reliability, monitoring, and lifecycle management.
- Process automation: Identify manual or fragmented workflows and design durable automation solutions using Python, Go, or no-code tools.
- Office hours and intake support: Partner in weekly AI enablement sessions and help turn identified use cases into repeatable, supportable workflows, or tools.
- Security and governance partnership: Work closely with Security to implement safe patterns for authentication, authorization, token handling, data protection, and production readiness for AI-enabled workflows.
- Infrastructure and engineering practices: Use Terraform, cloud infrastructure, and version-controlled delivery practices to manage the systems that support internal AI enablement.
- Documentation and training: Create clear documentation, reusable patterns, and technical guidance that help teams adopt AI responsibly and effectively.
- Cross-functional collaboration: Partner with IT, Security, Engineering, and business teams to prioritize opportunities, collect feedback, and continuously improve solutions.
- Continuous improvement: Balance quick wins with long-term maintainability, using feedback and operational data to improve quality, adoption, and scale.
Benefits
- Remote-First Culture
- Competitive Salary & Equity
- Comprehensive Medical, Dental, and Vision Plan Offerings
- Life and disability coverage including voluntary options
- Parental Leave - up to 8 weeks (320 hours) of paid parental leave based on meeting eligibility requirements
- 401K Company Contribution
- Work-from-home stipend
- Annual Professional Development Fund
- Be Well Program
- Paid Volunteer Service Hours
- Referral Program and Reward
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What This Job Offers
Job Type
Full-time
Career Level
Senior
