Job Description:
• You will deploy AI solutions that are practical, safe, and built to last. This means working across the full stack of modern AI implementation: custom integrations, automation workflows, LLM-powered tools, and hands-on enablement with client teams.
• You will build the connectors, agents, and workflows that make AI actually work inside our clients' existing systems - and you will help our internal team move faster with AI as well.
• You are embedded in client engagements and internal projects simultaneously. On the client side, you are building custom AI integrations, deploying workflows, and running enablement sessions that drive real adoption.
• Internally, you are the person who helps the team move faster by identifying and deploying new AI capabilities as they emerge.
• No two weeks look the same. One week you are building a custom MCP connector to pipe client data into an AI workflow. The next you are deploying a Make automation that replaces hours of manual work. The week after that you are running a training session that changes how a team of 10 people does their job.
Requirements:
• Applied AI expertise - You are deeply familiar with the current AI landscape and know how to deploy it practically. You follow what is happening with LLMs closely and apply new capabilities fast.
• Builder mentality - You do not just advise. You build the integrations, configure the tools, and deploy the systems yourself.
• Technical breadth - You are comfortable working across APIs, automation platforms, and AI frameworks without needing a dedicated engineer to support you.
• Autonomy - You can identify what needs to be built, figure out how to build it, and deliver without being micromanaged.
• Enablement mindset - You genuinely enjoy helping others use AI effectively and can translate complex capabilities into practical habits for non-technical teams.
• Curiosity - The field moves fast. You move with it.
• Communication skills - You can explain AI concepts clearly to non-technical stakeholders. Client-facing experience is a plus, not a requirement.
• Professional English fluency - B2 level at a minimum.
• 2-5 years of experience deploying AI tools and systems in a professional context
• Background in any industry is welcome. Experience in professional services, consulting, or agencies is a strong plus, as is prior client-facing experience
• Ideally from a company of 50-200 people where you wore multiple hats
• Hands-on experience with LLMs and the Claude and/or Google AI ecosystem (e.g. Gemini, AI Studio, Claude API)
• Experience building and deploying automation workflows (e.g. Make, n8n, Zapier)
• Experience working with REST APIs and building custom integrations
• Familiarity with MCP (Model Context Protocol) or similar custom connector frameworks is a strong plus
• Experience building custom AI agents, GPTs, or AI-powered tools
• Comfort working with CRM and operational data as AI inputs
• Experience helping teams adopt and embed AI tools into their daily workflows
Benefits:
• Competitive salary
• Performance-based bonus & promotion path
• Flexible benefits
• Career-defining growth investment: we spent over $200,000 on team development last year - executive coaching, certifications, and training that accelerates your career beyond any traditional path