AI Platform Context Architect

AgileEngine, LLC.; Austin (TX); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Professional growth

Competitive USD-based compensation

A selection of exciting projects

Flextime

Job summary

AgileEngine is seeking an AI Platform Context Lead to build the context and knowledge layer behind an enterprise AI ecosystem. You will design, implement, and govern knowledge graphs, semantic retrieval, and agent integrations across Slack, Google Workspace, Glean, and AI assistants.

Lead the evaluation and governance of answer quality, scalability, and security while driving reusable self-service patterns and cross-team collaboration to ensure robust context grounding and reliable production

Qualifications

• Authorized to work in the US for any employer; visa sponsorship not available.
• 6+ years of development experience with hands-on Tech Lead work.
• Designed or owned end-to-end knowledge graph or enterprise context architecture.
• Experience building production AI agents, skills, or integrations using MCP, function calling, RAG, and enterprise search.
• Able to distinguish wrong retrieval from right retrieval and prioritize fixes by impact.
• Hands-on with enterprise SaaS/AI platforms: Slack, Google Workspace, Glean, Claude, ChatGPT.
• Strong systems administration: identity/access management, monitoring, and incident response.
• Experience facilitating cross-functional work and turning questions into reusable checklists.
• Excellent troubleshooting, technical writing, and stakeholder communication; able to lead through influence.

Responsibilities

• Design and continually improve the company context and knowledge graph grounding search and agent responses.
• Review agent outputs for context gaps and convert findings into a prioritized backlog.
• Maintain cross-team visibility to fix systemic context gaps architecturally.
• Collaborate with subject-matter experts to design AI agents, skills, prompts, and workflows.
• Decide whether a need is best solved by a skill, workflow, connector, or knowledge-graph grounding.
• Translate platform strategy into designs, integrations, and production-ready capabilities.
• Ensure implementations are scalable, secure, and aligned with standards.
• Build and maintain connectors, APIs, and RAG/semantic-search patterns with source permissions.
• Develop discovery tooling and question sets for teams to scope new AI use cases.
• Enable teams to curate and maintain context via tooling and guidance.
• Establish testing and evaluation for agent output quality, reliability, and safety.
• Configure, administer, and maintain Slack, Google Workspace/Gemini, Glean, and AI assistants.
• Apply access-management, monitoring, and change-control; troubleshoot platform issues.
• Implement controls for access, data retention, and sensitive-data handling with security teams.
• Flag connectors needing elevated access for security review.
• Maintain documentation, runbooks, and vendor coordination.
• Maintain incident-response and service-continuity procedures.
• Drive continuous improvement in platform reliability, search quality, and cost efficiency.

Skills

Tech Lead

Knowledge graph design

AI agents / MCP / RAG

SaaS / AI platforms

Identity / access management

Tools

Slack

Google Workspace

Glean

Claude

ChatGPT

Job description

AgileEngine is seeking an AI Platform Context Lead to build the context and knowledge layer behind an enterprise AI ecosystem. You will design, implement, and govern knowledge graphs, semantic retrieval, and agent integrations across Slack, Google Workspace, Glean, and AI assistants.

Lead the evaluation and governance of answer quality, scalability, and security while driving reusable self-service patterns and cross-team collaboration to ensure robust context grounding and reliable production