Note: The job is a remote job and is open to candidates in USA. TENEX.AI is an AI-native, automation-first Managed Detection and Response (MDR) provider. The AI Enablement Engineer will partner with teams across the company to build and maintain TENEX's internal AI platform, ensuring that all employees can leverage AI tools effectively to enhance their work.
Responsibilities
- Build and evolve TENEX's internal AI platform: a reusable foundation of tools, custom skills, Claude Projects, integrations, and department-specific specialists that scale AI impact across every team
- Partner with teams across TENEX (Sales, Customer Success, Marketing, Finance, Legal, HR, Detection Engineering, Security Operations, Forward-Deployed Engineering) to surface needs that shape our internal AI platform roadmap
- Own and execute against a published roadmap. Predictable, visible execution is a core expectation of this role
- Maintain, expand, and refine our AI work companion based on user feedback and emerging needs
- Build integrations between Claude and our internal tools (e.g., Ashby, Wonderlic, Fireflies, Asana, Google Chat) using webhooks, MCP connectors, and APIs. Favor reusable patterns over one-off solutions
- Run enablement: training sessions, documentation, AMAs, and 1:1 onboarding to help every TENEX'er become more AI-native
- Contribute to AI governance, monitoring, and security tooling decisions as TENEX scales its AI usage
Skills
- Anthropic Claude ecosystem expertise
- Has shipped real work using Anthropic's Claude products, including Claude.ai, Claude Code, Cowork, Projects, custom skills, and MCP connectors. Tutorial-level familiarity is not enough. You should be able to point to things you've built that are actually in use by other people
- Comfortable using Claude Code for technical work, including building scripts, integrations, and tooling
- Strong prompt engineering instincts and an ability to translate vague user needs into clear, scoped AI workflows
- Familiarity with Gemini Enterprise is a plus, as we also use it
- 5+ years of experience in software development. Python is preferred. Comfort with REST APIs, webhooks, and JSON-based integrations is required
- Comfortable working across the integration surface: reading API docs, configuring webhooks, debugging auth flows, building lightweight services that connect tools together
- Familiarity with version control (Git/GitHub) and modern engineering practices
- Demonstrated ability to design and build for reuse. You see common patterns across requests and abstract them into platform capabilities rather than building one-off solutions every time
- Strong instincts for protecting sensitive data. You understand that internal AI workflows must be designed with strict guardrails around what data they can access, especially when customer information, employee information, or internal IP could be in scope. You build accordingly
- Demonstrated production experience working with sensitive data (PII, customer data, internal IP, or regulated data). You can speak to specific decisions you've made to protect it
- Familiarity with AI-specific security risks: prompt injection, data leakage to third-party LLMs, unsanctioned tool use, output misuse. You consider these risks proactively, not retroactively
- Working knowledge of secrets management, secure SDLC practices, and the basics of compliance frameworks (e.g., SOC 2)
- Can sit with a CSM, finance lead, recruiter, or executive and translate their workflow into something AI can help with, without condescension, without overengineering, and without losing patience
- Comfortable presenting to groups: running training sessions, demoing new tools at all-hands meetings, hosting AMAs
- Strong written communication. You will write documentation, policy drafts, status updates, and company-facing announcements
- Comfortable saying 'no' or 'not yet' when an idea isn't ready, scoped, or appropriately resourced
- Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience
- Anthropic certifications, AI/ML certifications, or security-related credentials are a plus but not required
- Experience building or maintaining an internal AI platform at another company
- Familiarity with Asana, Atlassian (Jira/Confluence), Google Chat, Google Workspace, Salesforce, Ashby, or other common B2B SaaS tools we integrate with
- Background in change management, technical writing, or internal enablement
- Experience with cybersecurity, even at a basic level, since several of our internal workflows involve our security and detection teams
- Hands-on experience with AI governance, AI security tooling, or AI usage monitoring platforms
Company Overview