AI Platform Context Lead - Flexible Remote & Growth

AgileEngine, LLC.; Metropolitana; Presencial; COP 248.316.000 - 372.474.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Professional growth

Competitive USD compensation

Exciting projects

Flextime

Descripción de la vacante

AgileEngine, LLC. is seeking an AI Platform Context Lead to build the knowledge layer behind an enterprise AI ecosystem.

You will design and maintain the context and knowledge graph, integrate AI agents across Slack, Google Workspace, and other tools, and improve answer quality through governance and reusable patterns. You will partner with SMEs to design, test, and maintain agents, prompts, and workflows; decide how to solve needs with skills, workflows, connectors, or grounding; and ensure

Formación

• 6+ years of experience in development roles and hands-on experience as a Tech Lead.
• Has designed and/or owned a knowledge graph or enterprise context/retrieval architecture end to end.
• Demonstrated experience building production-quality AI agents, skills, or integration using MCP, function calling, RAG, and enterprise search.
• Can distinguish "wrong retrieval" from "right retrieval, missing context" in an eval trace, and prioritize fixes by business impact.
• Hands-on experience administering or engineering enterprise SaaS, search, or AI platforms (e.g., Slack, Google Workspace, Glean, Claude, ChatGPT).
• Strong systems-administration background, including identity/access management, configuration, monitoring, and incident response.
• Experience working across multiple business functions, with the ability to turn "what should we ask before we start" into a checklist others can use unsupervised.
• Strong troubleshooting, technical writing, and stakeholder-communication skills, with the ability to lead through influence without direct authority.

Responsabilidades

• Design, curate, and continuously improve the company context and knowledge graph grounding search and agent responses.
• Review agent outputs and backlogs to fix context gaps with business impact in mind.
• Maintain cross-team visibility to fix systemic context gaps architecturally.
• Design, build, test and maintain AI agents, skills, prompts, and workflows using MCP, function calling, and RAG frameworks.
• Decide whether a need is best solved by a skill, workflow, connector, or knowledge-graph grounding.
• Translate platform strategy into technical designs and production-ready capabilities.
• Ensure implementations are scalable, secure, and compliant 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.
• Empower teams to curate context via tooling and guidance.
• Establish testing and evaluation practices for agent output quality and safety.
• Configure and maintain Slack, Google Workspace/Gemini, Glean, and other AI assistants.
• Apply access-management, monitoring, and change-control best practices; troubleshoot complex issues.
• Implement data handling controls with security, privacy, and compliance partners.
• Flag elevated access needs early and route to security for 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.

Conocimientos

Tech Lead

Knowledge graph

AI agent integration

Enterprise SaaS

IAM / access control

Cross-functional collaboration

Technical writing

Stakeholder communication

Herramientas

Slack

Google Workspace

Glean

Claude

ChatGPT

Descripción del empleo

AgileEngine, LLC. is seeking an AI Platform Context Lead to build the knowledge layer behind an enterprise AI ecosystem.

You will design and maintain the context and knowledge graph, integrate AI agents across Slack, Google Workspace, and other tools, and improve answer quality through governance and reusable patterns. You will partner with SMEs to design, test, and maintain agents, prompts, and workflows; decide how to solve needs with skills, workflows, connectors, or grounding; and ensure