AI Tech Lead

Preferred Time Zone: CT

Must-Have Skills:

Demonstrated experience building and maintaining production-quality AI agents, skills, assistants, workflows, or integrations. Strong understanding of AI application concepts, including agents and agentic workflows; skills, tools, and function calling; Model Context Protocol; prompt and context design; retrieval-augmented generation; enterprise search and data connectors; grounding, citations, memory, and context management; model and agent evaluation; and AI safety and access controls. Proven ability to move solutions from proof of concept to stable, supportable production services. Experience integrating systems through APIs, SDKs, webhooks, identity services, or automation platforms. Working knowledge of enterprise security, privacy, compliance, and data-governance principles. Significant hands-on experience administering or engineering enterprise SaaS, collaboration, productivity, search, automation, or AI platforms. Practical experience with several of the following: Slack, Google Workspace, Gemini for Workspace, Glean, Claude, ChatGPT, or comparable enterprise AI products. Strong knowledge of systems-administration practices, including identity and access management, role-based permissions, configuration management, logging, monitoring, incident response, and change management. Strong troubleshooting, technical writing, architecture documentation, and stakeholder-communication skills. Ability to lead technically through expertise and influence without direct people-management authority.

Nice-to-Have Skills:

Experience with single sign-on, SCIM provisioning, OAuth, service accounts, delegated authorization, and enterprise identity providers. Familiarity with cloud platforms, infrastructure as code, source control, CI/CD, secrets management, and observability. Software development experience with Python, TypeScript, JavaScript, or similar languages. Experience creating MCP servers or integrating MCP-compatible clients and tools. Experience operating an enterprise AI platform or supporting an internal AI enablement program. Familiarity with responsible-AI practices, AI security frameworks, and model or agent evaluation methodologies.

Notes: No direct reports. This role is more leading through influence by setting standards, mentoring other admins/engineers, etc.

Strong preference in AI technology depth, with lighter platform administration experience rather than the other way around.

Scope of Work: The AI Platform Technical Lead is the hands-on technical owner of the organization's general-purpose, AI-enabled collaboration ecosystem, spanning Slack, Google Workspace with Gemini, Glean, and general-purpose AI assistants such as Claude and ChatGPT. Working within the strategy and priorities established by the organization, this role translates platform direction into secure, scalable, and supportable technical solutions. The Technical Lead configures, maintains, and improves these platforms based on data and feedback; builds agents and reusable skills; implements integrations; establishes technical patterns; and guides other contributors through technical expertise and example.

Key Responsibilities:

·       Design, build, test, and maintain AI agents, skills, prompts, tools, workflows, and automations.

·       Build AI solutions using MCP, function calling, APIs, agents, and integration frameworks.

·       Translate business needs into technical designs, prototypes, and production-ready AI capabilities.

·       Build secure integrations across Slack, Google Workspace/Gemini, Glean, AI assistants, and enterprise systems.

·       Develop APIs, data connectors, webhooks, search integrations, and RAG/semantic-search solutions.

·       Ensure AI systems preserve source-system permissions, access controls, data security, and governance requirements.

·       Test and evaluate AI solutions for quality, reliability, safety, performance, and data grounding.

·       Administer and optimize enterprise AI platforms, including access, configurations, integrations, monitoring, and lifecycle management.

·       Troubleshoot complex AI platform, integration, connector, and data-retrieval issues.

·       Establish standards for AI agents, integrations, configurations, testing, deployment, and security.

·       Lead technical solution reviews, mentor contributors, and serve as the senior technical escalation point.

·       Evaluate emerging AI capabilities and provide technical recommendations to platform leadership.