AI Implementation Strategist

About the role

RepStack is looking for a hands‑on AI Implementation Strategist to design, build, and operate AI‑powered workflows that eliminate manual effort for both internal teams and clients. This role focuses on delivering production‑ready systems rather than research or model training.

Key responsibilities

• Build agentic systems that select tools, manage context, and execute multi‑step tasks.
• Implement MCP (or equivalent) to handle tool selection, context, and memory in production.
• Translate business requirements into scoped AI solutions from prototype through pilot to production.
• Integrate AI with CRMs, APIs, webhooks, and data sources such as GoHighLevel, Slack, and Google Workspace.
• Develop and version prompts, orchestration flows, and Retrieval‑Augmented Generation (RAG) pipelines.
• Set up monitoring for hallucinations, regressions, latency, and cost.
• Document builds with SOPs/runbooks so non‑technical teams can operate them.
• Collaborate with Talent Acquisition, Customer Success, and Operations to automate high‑impact workflows.
• Stay up‑to‑date on models, tools, and agentic patterns and apply learnings to improve systems.

Required profile

• Bachelor's degree in Computer Science, Engineering, or related field, or equivalent practical experience.
• 2+ years building and running production software or automation systems.
• Hands‑on experience with real agentic AI systems (tool selection, multi‑step execution).
• Experience with MCP or similar approaches for tools, context, and memory.
• Solid understanding of AI model characteristics, prompt design, latency, cost, and quality trade‑offs.
• Experience integrating AI with APIs, databases, and real‑world services.
• Ability to evaluate AI beyond accuracy, considering reliability, hallucination risk, traceability, and safety.
• Knowledge of scaling concerns such as latency, cost optimization, caching, parallelization, and RAG vs. fine‑tuning.
• Proven track record taking AI systems from prototype to production.
• Comfortable working autonomously in a small, empowered team.
• Strong written and spoken English for US/Canada client‑facing work.

Required skills

• MCP (or equivalent) for tool, context, and memory management.
• Agentic AI system development and prompt engineering.
• Retrieval‑Augmented Generation (RAG) pipeline construction.
• API integration with CRMs and services (e.g., GoHighLevel, Slack, Google Workspace).
• Monitoring and evaluation of AI outputs for hallucinations, latency, and cost.
• Documentation creation (SOPs/runbooks) for non‑technical users.

What we offer

• Innovative pay scale with performance‑based bonuses, client onboarding and retention bonuses.
• Health insurance and referral bonuses.
• Bi‑annual performance appraisals with career growth feedback.