AI Platform Context Lead (Remote + Flextime)

AgileEngine, LLC.; Tampa (FL); Hybrid; USD 140,000 - 210,000; Full time

Benefits offered by this job

Professional growth

Competitive compensation

A selection of exciting projects

Flextime

Job summary

AgileEngine is seeking an AI Platform Context Lead to architect and govern the knowledge graph and context layer that grounds enterprise AI. You will collaborate with SMEs to design, build, test, and maintain AI agents, skills, and workflows using MCP, function calling, and RAG approaches.

You will translate platform strategy into scalable, secure designs, maintain tooling and documentation, and drive continuous improvement in reliability and cost efficiency.

Qualifications

• 6+ years in development roles with hands-on Tech Lead experience.
• Ownership of knowledge-graph or enterprise context architecture end-to-end.
• Production AI agents, skills, or integrations using MCP, RAG, and enterprise search.
• Ability to differentiate wrong vs missing-context retrieval and fix high-impact gaps.
• Experience with enterprise SaaS platforms and IAM, monitoring, and incident response.

Responsibilities

• Design and improve the knowledge graph grounding search and agent responses.
• Review agent outputs and backlog fixes to reduce context gaps.
• Maintain cross-team visibility to fix context gaps architecturally.
• Collaborate with SMEs to build AI agents, prompts, and workflows.
• Decide if a need is best solved by a skill, workflow, connector, or graph grounding.
• Translate strategy into designs and production-ready plans.

Skills

6+ years experience

Tech Lead

Knowledge graph design

AI agents integration

MCP function calling

RAG and semantic search

Enterprise SaaS platforms

Slack, Google Workspace

Tools

Slack

Google Workspace

Glean

Claude

ChatGPT

Job description

AgileEngine is seeking an AI Platform Context Lead to architect and govern the knowledge graph and context layer that grounds enterprise AI. You will collaborate with SMEs to design, build, test, and maintain AI agents, skills, and workflows using MCP, function calling, and RAG approaches.

You will translate platform strategy into scalable, secure designs, maintain tooling and documentation, and drive continuous improvement in reliability and cost efficiency.