FREE ACCESS
5,000–10,000 jobs/day
See all jobs on Scoutfield
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
AI Engineering Enablement & Adoption Coach
SmartLogic. Assess current AI usage, engineering workflows, skill levels, pain points, and opportunities across the team .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates extensive experience in AI-assisted development, with a focus on establishing standards, workflows, and practices that enhance software quality and maintainability. Capable of coaching engineering teams on effective AI integration while ensuring compliance with security and privacy standards.
Highest-signal resume keywords
AI Engineering ConsultingAI-Assisted DevelopmentSoftware Engineering StandardsCoaching and Communication SkillsWorkflow Development
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
AI Tools EvaluationAgentic Coding ToolsSoftware Quality AssuranceArchitecture StandardsMaintainability PracticesTesting StandardsCode Review ProcessesInternal Tooling DevelopmentRisk Assessment of AIMetrics Evaluation
Soft Skills
Coaching SkillsCommunication Skills
Industry Keywords
AI AdoptionSoftware DeliveryClient IP ManagementConfidentiality ObligationsSensitive Health Information
About the role
Key responsibilities & impact- Assess current AI usage, engineering workflows, skill levels, pain points, and opportunities across the team
- Identify highest-value use cases for AI-assisted development
- Evaluate AI tools and practices and recommend where to standardize, experiment, or avoid adoption
- Develop an AI engineering enablement upskill strategy and prioritized roadmap
- Establish repeatable practices, standards, playbooks, workflows, or reusable tooling across project teams
- Upskill developers and Staff Engineers through hands-on application of AI in real development workflows
- Ensure AI-assisted development maintains standards for architecture, maintainability, testing, code review, security, privacy, and quality
- Establish baselines and measures for whether AI adoption improves software delivery profit margin
- Help SmartLogic build software faster and better through responsible AI-assisted development
- Account for client IP, confidentiality obligations, sensitive health information, and varying AI permissions across client projects
Requirements
What you’ll need- Experienced AI engineering consultant or practitioner
- Staff Engineer-level software engineering depth and judgment
- Deep, hands-on experience using AI-assisted development and agentic coding tools in real production codebases
- Demonstrated ability to help engineers use AI without lowering standards for architecture, maintainability, testing, security, code review, and software quality
- Experience helping engineering teams adopt AI
- Experience developing practical workflows, standards, playbooks, or internal tooling used by other engineers
- Strong understanding of the risks and limitations of AI-generated software, including when AI assistance should not be used
- Experience evaluating AI's impact on software delivery without relying solely on superficial adoption metrics
- Strong coaching and communication skills
- Ability to sign an NDA
- Proposal must include relevant experience, similar engagements and outcomes, proposed approach, performing personnel and technical background, engagement structure and timeline, pricing and payment structure, and references or case studies if available