Request for Proposal: AI Engineering Enablement & Adoption Coach

About SmartLogic SmartLogic is a U.S.-based custom software development consultancy serving clients since 2005. We build and maintain custom web and mobile applications and are looking to intentionally modernize how our engineering team builds software through effective, responsible use of AI-assisted development tools and practices. What We Are Looking For We are seeking an experienced AI engineering consultant or practitioner to help SmartLogic move from individual, ad hoc AI usage to a more intentional, repeatable, team-wide approach to AI-assisted software development. This is not a management role or an outsourced engineering leadership position. We are looking for someone who can work directly with our Staff Engineers and developers to assess how we work today, identify meaningful opportunities for improvement, and help our team build the skills, standards, and workflows needed to use AI effectively in production software development. This is intended to help upskill our existing staff with modern AI practices. Business Objective Our goal is simple: Build high-quality software faster and better than we can using traditional development methods alone. We believe effective AI adoption can help us: Increase engineering capacity without increasing headcount at the same rate. Improve delivery efficiency and project margins. Reduce writedowns, rework, and avoidable delivery costs. Keep our engineering team current and competitive as software development practices evolve. Create consistent, responsible AI practices across project teams. We do not expect a consultant to arrive with a predetermined AI ROI formula. Part of this engagement is helping us establish realistic baselines and determine what measures are actually useful for evaluating improvements in delivery speed, quality, and engineering capacity. Scope of Work We expect the engagement to include: Assess: Current AI usage, engineering workflows, skill levels, pain points, and opportunities across the team. Identify the highest-value use cases for AI-assisted development within our environment. Evaluate AI tools and practices and recommend where SmartLogic should standardize, experiment, or avoid adoption. Plan: Develop a practical AI engineering enablement upskill strategy and prioritized roadmap. Establish repeatable practices, standards, playbooks, workflows, or reusable tooling that can be adopted across project teams. Coach: Upskill developers and Staff Engineers through hands-on application of AI in real development workflows that shows measured efficiencies. Ensure AI-assisted development maintains strong engineering standards around architecture, maintainability, testing, code review, security, privacy, and quality. Measure: Help establish appropriate baselines and measures for assessing whether AI adoption is meaningfully improving software delivery profit margin. Expected Outcomes At the end of the initial engagement, we want to have: A clear…