AI Platform Context Lead ID84742

AgileEngine, LLC.; Fort Lauderdale (FL); Sur place; USD 160 000 - 210 000; Plein temps

Avantages offerts par ce poste

Professional growth

Competitive compensation

Exciting projects

Flextime

Résumé du poste

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

You will design, curate, and continuously improve the knowledge graph grounding search and agent responses, while collaborating with experts across teams to implement scalable, secure, and production-ready capabilities. You will evaluate platform capabilities, maintain plugins and workflows, and ensure the reliability and governance of AI solutions

Qualifications

• Must have 6+ years in development roles with hands-on Tech Lead experience.
• Experience designing/owning a knowledge graph or enterprise context/retrieval architecture end-to-end.
• Proven track record building production-quality AI agents, skills, or integrations using MCP, function calling, RAG, and enterprise search.
• Ability to distinguish incorrect retrieval from missing context and prioritize fixes by business impact.
• Hands-on experience with enterprise SaaS, search, or AI platforms (Slack, Google Workspace, Glean, Claude, ChatGPT).
• Strong identity/access management, configuration, monitoring, and incident response skills.

Responsabilités

• Design and maintain the knowledge graph grounding search and agent responses, with a baseline for accuracy and efficiency.
• Review agent outputs to identify missing or misaligned context and backlog fixes by business impact.
• Maintain cross-team visibility to fix systemic context gaps architecturally.
• Collaborate with SMEs to design, build, test, and maintain AI agents, skills, prompts, and workflows.
• Decide whether needs are 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 proper permissions.
• Create discovery tooling and question sets to scope new AI use cases.
• Enable teams to curate their own context via tooling and guidance.
• Establish testing/evaluation practices for agent output quality, reliability, and safety.
• Configure and maintain Slack, Google Workspace, Glean, and other AI assistants.
• Apply access-management, monitoring, and change-control best practices.

Connaissances

6+ years of experience in development

Tech Lead

knowledge graph

AI agents

retrieval augmentation

integrations

troubleshooting

stakeholder communication

scale and security

Outils

Slack

Google Workspace

Glean

Claude

ChatGPT

Description du poste

Fort Lauderdale, United States | Posted on 09/14/2026

AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.

WHY JOIN US

If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!

ABOUT THE ROLE

We are looking for an AI Platform Context Lead to build the context and knowledge layer behind an enterprise AI ecosystem. The role combines knowledge-graph design, semantic retrieval, RAG, and agent integrations across Slack, Google Workspace, Glean, and AI assistants. You will improve answer quality through evaluation, governance, and reusable self-service patterns.

WHAT YOU WILL DO

• - Design, curate, and continuously improve the company context and knowledge graph that grounds search and agent responses, managing schema, coverage, freshness, and retrieval quality as an ongoing responsibility rather than a one-time build, with a stated accuracy and efficiency baseline that improves over time.
• - Review agent and skill outputs to catch cases where a result missed user intent because the underlying context was missing or wrong, and turn those findings into a prioritized backlog of fixes so that intent-breaking context gaps are resolved rather than left to resurface.
• - Maintain enough cross-team visibility that a systemic context gap gets fixed once, architecturally, instead of being patched repeatedly.
• - Partner with subject-matter experts to design, build, test, and maintain AI agents, skills, prompts, and workflows using MCP, function calling, and comparable frameworks.
• - Decide whether a need is best solved by a skill, workflow, connector, or knowledge-graph grounding, based on where the logic belongs rather than what is fastest to ship.
• - Translate platform strategy into technical designs, integrations, and implementation plans, and turn pilots into reliable, production-ready capabilities by evaluating platform capabilities.
• - Ensure implementations are scalable, secure, and aligned with organizational standards.
• - Build and maintain connectors, APIs, and RAG/semantic-search patterns while preserving source-system permissions.
• - Build and maintain the discovery tooling and question sets other teams use to scope new AI use cases on their own, reducing the hands-on involvement required from this role.
• - Enable functional groups to curate and maintain their own context in the way that works best for them through tooling, patterns, and guidance, rather than one-size-fits-all mandates.
• - Establish testing and evaluation practices for agent output quality, reliability, and safety.
• - Configure, administer, and maintain Slack, Google Workspace/Gemini, Glean, and other AI assistants.
• - Apply access-management, monitoring, and change-control best practices, and troubleshoot complex platform issues.
• - Implement technical controls for access, data retention, and sensitive-data handling in partnership with security, privacy, and compliance teams.
• - Flag connectors needing elevated or write access early, during design, and route them to security for review.
• - Maintain technical documentation, runbooks, and vendor coordination.
• - Maintain incident-response and service-continuity procedures.
• - Drive continuous improvement in platform reliability, search quality, and cost efficiency over time.

MUST HAVES

• - You must be authorized to work for ANY employer in the US (e.g., Green card holders, TN visa holders, GC EAD, H4 EAD, U4U with EAD), as we are unable to sponsor or take over employment visa sponsorship at this time;
• - 6+ years of experience in development roles, with hands-on experience as a Tech Lead.
• - Has designed and/or owned a knowledge graph or enterprise context/retrieval architecture end to end, not merely queried one that someone else built.
• - Demonstrated experience building production-quality AI agents, skills, or integrations 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.

PERKS AND BENEFITS

• - Professional growth: Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps.
• - Competitive compensation: We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities.
• - A selection of exciting projects: Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands.
• - Flextime: Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office – whatever makes you the happiest and most productive.