AI Developer Productivity Consultant

HMG America LLC is the best Business Solutions focused Information Technology Company with IT consulting and services, software and web development, staff augmentation and other professional services. One of our direct clients is looking for AI Developer Productivity Consultant in USA/Canada. Below is the detailed job description.

Role Overview:

• Title: AI Developer Productivity Consultant (AI IDE & Copilot Specialist)
• Experience Level: 10+ years total software engineering / dev productivity experience, including 2 3+ years with GenAI tooling
• Employment Type: Full-time
• Location: Canada

• Own the strategy, evaluation, and rollout of AI-powered IDE and copilot tools across engineering teams, with a clear focus on measurable outcomes such as cycle time, PR throughput, and defect rates.
• Continuously track, assess, and communicate new releases, features, and roadmap items in AI IDE tools (e.g., MCP, Skills, Plugins, SubAgents, Agent Teams) and translate them into concrete use cases for the organization.
• Design and implement MCP (Model Context Protocol) integrations and managed MCP server capabilities to connect AI assistants with internal codebases, documentation, APIs, and tools in a secure and governed way.
• Evaluate and integrate plugins, extensions, and marketplace offerings (e.g., Copilot extensions, IDE plugins, workflow bots) to enhance developer workflows from coding to testing, debugging, and deployment.
• Develop and maintain prompt engineering best practices for code generation, refactoring, test authoring, documentation, and code review scenarios, tailored to the organization's tech stack and standards.
• Establish usage guidelines, guardrails, and coding standards for AI-assisted development, including patterns for safe acceptance of suggestions, security considerations, and IP/compliance constraints.
• Partner with engineering leadership, team leads, and architects to identify high-impact workflows where agents, sub-agents, and agent teams can reduce development time (e.g., scaffolding services, test generation, migration scripts).
• Design and deliver hands-on training sessions, workshops, and office hours to upskill developers on effective usage of AI IDE tools, including advanced capabilities like MCP-based context, agent orchestration, and tool calling.
• Create and maintain demos, reference implementations, and starter templates that showcase best-practice usage of AI assistants within the organization's languages, frameworks, and CI/CD pipelines.
• Define and implement measurement frameworks and dashboards (e.g., DORA metrics, PR throughput, review time, cycle time) to quantify the impact of AI tooling and iterate based on data.
• Collaborate with Platform Engineering, Security, and IT to ensure AI IDE tools are integrated safely into the SDLC, with appropriate access controls, observability, and governance in place.
• Act as the internal subject-matter expert on AI-assisted software development, advising on vendor selection, licensing, experimentation design, and long-term roadmap for developer productivity.

• 10+ years of professional experience in software engineering, developer productivity/DevEx, platform engineering, or related roles in modern engineering organizations.
• 2 3+ years of hands-on experience with GenAI tools in software development contexts, including at least one major AI coding assistant (e.g., GitHub Copilot, Claude Code, Cursor, Gemini Code Assist, Codeium) in day-to-day workflows.
• Strong practical expertise in prompt engineering for code: writing effective prompts for generation, refactoring, debugging, test creation, and multi-step workflows; experience iterating prompts based on model behavior and evaluation.
• Demonstrated experience designing and implementing developer tools, extensions, or integrations for at least one major IDE/editor (e.g., VS Code, JetBrains IDEs, Neovim) or internal engineering platform.
• Solid understanding of GenAI concepts and architecture (LLMs, embeddings, RAG, tools/functions, agents, context management) and how they apply to developer workflows.
• Hands-on experience integrating AI systems with internal services or platforms via APIs, SDKs, or protocols (experience with MCP or similar context/tooling protocols strongly preferred).
• Strong programming skills in at least one mainstream language (e.g., TypeScript/JavaScript, Python, Java, C#, Go), with the ability to build reference applications, scripts, and POCs quickly.
• Experience defining and tracking engineering productivity metrics (e.g., DORA metrics, PR throughput, lead time, MTTR) and running experiments or pilots to measure impact of new tools and practices.
• Excellent facilitation and communication skills; proven ability to train, mentor, and influence senior engineers and tech leads on new tools and practices.
• Familiarity with secure software development, code quality and testing practices, and common concerns around AI-generated code (security, reliability, intellectual property, privacy).

• Prior experience in a dedicated Developer Productivity, Developer Experience, or Platform Engineering role driving tooling and workflow change at scale.
• Experience rolling out GitHub Copilot (or similar) in enterprise environments, including policy definition, onboarding plans, and measurement of impact.
• Exposure to multi-agent frameworks, orchestration platforms, or agentic patterns applied to software engineering (e.g., automated refactoring agents, test-maintenance agents, documentation agents).
• Background working with large monorepos or complex microservice architectures and understanding of typical bottlenecks in such environments.
• Experience with cloud platforms and CI/CD tooling (e.g., GitHub Actions, GitLab CI, Azure DevOps, Jenkins) and integrating AI capabilities into these pipelines.