AI Implementation Strategist

Details

We are looking for a senior, technically strong AI Implementation Strategist to design, prototype, and deploy AI-driven workflows in real operational environments. This is not a general “AI consultant” role. We are looking for someone who can work hands‑on with AI coding tools, structured documentation, automation logic, prompts, workflows, APIs, and technical teams — and who can turn complex requirements into working AI-assisted systems.

• Senior-level experience in technical implementation, automation, AI tooling, software‑adjacent roles, product engineering, solution architecture, or technical project delivery.
• Hands‑on experience with Cursor or Zed.
• Strong familiarity with .md files, structured Markdown documentation, repositories, specifications, prompts, and technical notes.
• Solid understanding of LLMs, prompt engineering, AI-assisted development, AI agents, workflow automation, and API‑based integrations.
• Ability to read and understand technical documentation, implementation logic, and developer workflows.
• Strong analytical thinking with the ability to break down complex systems into clear implementation steps.
• Excellent written communication skills for creating technical documentation.
• Comfortable collaborating directly with technical teams and challenging implementation assumptions.
• High level of ownership, precision, and the ability to work independently.

• Experience with Git, Git Hub/Git Lab, JSON, YAML, REST APIs, webhooks, automation platforms, or low-code/no-code tools.
• Experience with customer support automation, e-commerce systems, CRM tools, chatbots, voicebots, or AI agents.
• Basic understanding of frontend and backend architecture.
• Experience creating internal documentation, SOPs, prompt libraries, or AI governance documentation.

This role is ideal for someone who is senior enough to understand the full implementation picture, technical enough to work close to the code, and structured enough to document everything clearly.

We are building practical AI systems that are used in production—not slide decks or abstract strategy.

• Design and implement AI-assisted workflows for real business operations.
• Work hands‑on with AI coding environments such as Cursor or Zed.
• Create, edit, and maintain structured .md documentation, prompt libraries, system instructions, implementation specifications, and workflow definitions.
• Translate operational problems into technical AI implementation plans.
• Prototype AI assistants, automation flows, internal tools, and agentic workflows.
• Collaborate closely with developers, product owners, system architects, and operational teams.
• Define implementation logic, data flows, fallback behavior, escalation rules, and quality‑control mechanisms.
• Test, debug, and refine AI outputs, prompts, automations, and integrations.
• Document decisions, workflows, edge cases, and technical requirements clearly and consistently.
• Support deployment, monitoring, iteration, and the long‑term maintainability of AI solutions.