AI Platform Context Lead - Knowledge Graph & RAG

Anyone Ai Inc.; Ciudad de Mendoza; Hybrid; ARS 230,602,000 - 322,843,000; Full time

Benefits offered by this job

Professional growth

Competitive compensation

Exciting projects

Flextime

Job summary

AgileEngine is seeking an AI Platform Context Lead to design and advance the context and knowledge layer behind an enterprise AI ecosystem. You will shape the knowledge graph, evaluate retrieval quality, and integrate agents across Slack, Google Workspace, Glean, and other AI tools.

You will collaborate with subject-matter experts to implement scalable, secure, and production-ready context solutions, drive continuous improvement, and lead through influence across multiple teams.

Qualifications

• 6+ years in development roles with hands-on Tech Lead experience.
• Designed or owned end-to-end knowledge graph/enterprise context retrieval architecture.
• Built production-quality AI agents, skills, or integrations using MCP, function calling, RAG, and enterprise search.
• Distinguish wrong vs right retrieval in eval traces and prioritize fixes by business impact.
• Administered or engineered enterprise SaaS, search, or AI platforms (Slack, Google Workspace, Glean, Claude, ChatGPT).
• Strong systems administration: identity/access management, config, monitoring, incident response.
• Experience working across multiple business functions and turning questions into reusable checklists.
• Strong troubleshooting and stakeholder communication; ability to lead through influence.

Responsibilities

• Design and curate the company context and knowledge graph for grounding search and agent responses with robust accuracy.
• Review agent outputs to identify missing or wrong context and feed fixes into a prioritized backlog.
• Maintain cross-team visibility to fix systemic context gaps architecturally.
• Collaborate with subject-matter experts to design, build, 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 designs, integrations, and production plans; scale pilots into reliable capabilities.
• Ensure implementations are scalable, secure, and align with standards.
• Build and maintain connectors, APIs, and RAG/semantic-search patterns with proper permissions.
• Create and manage discovery tooling and question sets for other teams to scope new AI use cases.
• Empower functional groups to curate their context with tooling and guidance; avoid one-size-fits-all mandates.
• Establish testing and evaluation practices for agent output quality, reliability, and safety.
• Configure and maintain Slack, Google Workspace/Gemini, Glean, and other AI assistants.
• Apply access-control, monitoring, and change-control practices; coordinate with security and compliance.
• Flag connectors needing elevated access early and route to security; maintain docs and runbooks.
• Maintain incident-response and service-continuity procedures.
• Drive platform reliability, search quality, and cost efficiency over time.

Skills

Tech Lead

Knowledge graph

Enterprise context

Production AI agents

Evaluation traces

SaaS platforms

Identity/access mgmt

Cross-functional

Troubleshooting writing

Tools

Slack

Google Workspace

Glean

Claude

ChatGPT

Job description

AgileEngine is seeking an AI Platform Context Lead to design and advance the context and knowledge layer behind an enterprise AI ecosystem. You will shape the knowledge graph, evaluate retrieval quality, and integrate agents across Slack, Google Workspace, Glean, and other AI tools.

You will collaborate with subject-matter experts to implement scalable, secure, and production-ready context solutions, drive continuous improvement, and lead through influence across multiple teams.