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SmartLogic
SmartLogic
11 – 50 Employees
ConsultingLogisticsMarketing
SmartLogic is a Baltimore-based software consultancy that builds custom web and mobile applications for organizations ranging from startups to Fortune 500 companies. Founded in 2005, the team combines modern technology with agile delivery practices to create scalable, responsive products tailored to each client’s goals. Its work has included a text-to-order food relief program for World Central Kitchen and usability improvements for the Baltimore City Health Department’s CHARMCare platform. SmartLogic works closely with clients as a technical partner across consulting, marketing, and logistics-related projects.
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AI Engineering Enablement and Adoption Coach

Coach SmartLogic’s engineering team in responsible AI-assisted development. Evaluate workflows and tools, guide adoption, and create scalable practices that improve software delivery while protecting quality, security, privacy, and client obligations.

USUnited StatesRemoteContractMiddleSeniorEnglish RequiredAI EngineerMachine Learning Engineer

Description

  • Review the team’s current AI usage, engineering workflows, capabilities, challenges, and opportunities
  • Determine the most valuable applications for AI-assisted software development
  • Assess AI tools and working methods, recommending what to standardize, test, or avoid
  • Create an AI engineering enablement strategy with a prioritized development roadmap
  • Build consistent practices, standards, playbooks, workflows, and reusable tools for project teams
  • Train developers and Staff Engineers through practical use of AI in live development workflows
  • Protect architecture, maintainability, testing, code review, security, privacy, and quality standards during AI-assisted development
  • Define benchmarks and metrics to evaluate AI’s effect on software delivery profit margin
  • Help SmartLogic deliver software more efficiently and effectively through responsible AI-assisted development
  • Manage considerations including client intellectual property, confidentiality, sensitive health data, and project-specific AI permissions

Requirements

  • Several years of experience as an AI engineering consultant or practitioner
  • Staff Engineer-level software engineering expertise and decision-making
  • Extensive hands-on experience with AI-assisted development and agentic coding tools in production codebases
  • Proven ability to help engineers use AI while preserving architecture, maintainability, testing, security, code review, and quality standards
  • Experience guiding engineering teams through AI adoption
  • Experience creating practical workflows, standards, playbooks, or internal tools for other engineers
  • Strong understanding of the risks and limitations of AI-generated software, including situations where AI assistance is inappropriate
  • Experience measuring AI’s effect on software delivery beyond basic adoption statistics
  • Excellent coaching and communication abilities
  • Willingness and ability to sign a non-disclosure agreement
  • Proposal covering relevant experience, comparable engagements and results, proposed approach, assigned personnel and technical background, engagement structure and timeline, pricing and payment terms, and available references or case studies

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