AI Platform Context Lead: Knowledge Graph & Retrieval

AgileEngine, LLC.; Mar del Plata; Híbrido; ARS 180.802.000 - 286.270.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Professional growth

Competitive USD compensation

A selection of exciting projects

Flextime

Descripción de la vacante

AgileEngine is seeking an AI Platform Context Lead to design and maintain the knowledge graph and grounding for an enterprise AI ecosystem. You will balance retrieval quality, governance, and scalable architectures across Slack, Google Workspace, Glean, and AI assistants.

Join a people‑first culture focused on delivering reliable, production‑ready AI capabilities, with a strong emphasis on cross‑team collaboration, testing, and security.

Formación

• 6+ years of development experience with hands-on Tech Lead.
• Designed or owned an end-to-end knowledge graph / enterprise context architecture.
• Experience building production AI agents, skills, or integrations using MCP, function calling, and RAG.
• Able to differentiate wrong vs missing-context retrieval and prioritize fixes.
• Hands-on with enterprise SaaS / AI platforms (Slack, Google Workspace, Glean, Claude, ChatGPT).
• Strong troubleshooting, technical writing, and stakeholder communication; influence-led leadership.

Responsabilidades

• Design, curate, and improve the knowledge graph and grounding for search and agent responses with ongoing quality baselines.
• Review agent outputs and backlog fixes to close context gaps and improve intent accuracy.
• Maintain cross-team visibility to ensure systemic context gaps are fixed architecturally.
• Collaborate with SMEs to design, test, and maintain 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 technical designs and production-ready capabilities.
• Ensure scalable, secure implementations aligned with standards.
• Build and maintain connectors, APIs, and RAG/semantic-search patterns.
• Develop tooling to scope new AI use cases with minimal hands-on involvement.
• Guide functional groups to curate their own context using tooling and guidance.
• Establish testing and evaluation practices for agent quality, reliability, and safety.

Conocimientos

Years of experience

Knowledge graph design

AI agents / MCP / function calling

SaaS / enterprise AI platforms

Retrieval evaluation & governance

Cross-functional collaboration

Troubleshooting & technical writing

Herramientas

Slack

Google Workspace

Glean

Claude

ChatGPT

Descripción del empleo

AgileEngine is seeking an AI Platform Context Lead to design and maintain the knowledge graph and grounding for an enterprise AI ecosystem. You will balance retrieval quality, governance, and scalable architectures across Slack, Google Workspace, Glean, and AI assistants.

Join a people‑first culture focused on delivering reliable, production‑ready AI capabilities, with a strong emphasis on cross‑team collaboration, testing, and security.