AI Dev Coach

Quick Facts

• Role: AI Dev Coach
• Focus: AI adoption and AI-enabled SDLC transformation for software engineering and DevOps teams

Description

The AI Dev Coach helps engineering organizations adopt and effectively use AI across the Software Development Lifecycle (SDLC) to improve productivity, software quality, and delivery performance. The role coaches and advises developers, DevOps engineers, architects, engineering managers, and technology leaders on identifying, implementing, governing, and scaling responsible AI solutions. Success is measured through KPIs/OKRs and ROI, supported by training and hands-on guidance using AI-assisted development tools.

Responsibilities

• Lead AI adoption initiatives across engineering, DevOps, platform engineering, QA, and product teams
• Run training sessions, workshops, office hours, and hands-on coaching for practical AI usage
• Mentor teams in using AI coding tools such as GitHub Copilot, Claude Code, and Cursor
• Integrate AI into daily engineering ways of working and promote AI literacy
• Drive AI-powered SDLC transformation from requirements through development, testing, deployment, and operations
• Assess team needs, identify high-value AI use cases, and define standards and governance frameworks
• Support scaling successful AI initiatives across multiple teams
• Define and monitor KPIs/OKRs and success metrics for AI adoption, productivity, and engineering efficiency
• Measure business impact and ROI and provide executive reporting on adoption progress and value realization

Requirements

• 5+ years of experience in a technical role (Software Developer, DevOps Engineer, Platform Engineer, QA Automation Engineer, SRE, or similar)
• Hands-on experience with AI-powered engineering tools (GitHub Copilot, Claude Code, Cursor, Microsoft 365 Copilot, or equivalent)
• Strong understanding of SDLC and DevOps methodologies
• Ability to lead training, workshops, and coaching for both technical and non-technical audiences
• Deep understanding of LLMs and AI ecosystems, including AI-assisted coding, content generation, agentic workflows, and automation
• Experience designing prompts, AI workflows, agents, and reusable AI solutions
• Knowledge of AI governance, security, compliance, and responsible AI practices
• Experience evaluating AI tools/platforms for quality, cost, risk, security, and regulatory requirements
• Analytical mindset to identify, measure, and prioritize AI use cases delivering business value

Benefits

Not specified in the provided posting.