AI Lead (Engineering focus)

Location Vietnam, Hanoi
Category
Consultancy
Working Model
Hybrid

Overview

About Our Partner

Our partner is a SaaS workforce management company designed to simplify employee scheduling, time and attendance tracking, and task management for businesses. The company has helped employers across all industries in 70+ countries optimize their workforce and improve operational efficiency. 

About BOT Model

Our BOT model provides a long-term solution for successfully delivering your product roadmap without outsourcing your software development. In just a few weeks, we can set up dedicated software development teams in Vietnam which will be steadily integrated in your organization and can eventually be fully transferred.

Reporting to the Director of Engineering, your key responsibilities will be to direct a team of dedicated engineers of varied experience levels.

Enabling your team as an inspiring Technical Manager, co-create the technical vision, strategy and technical roadmap planning and product definition for your team, alongside your technical leads and product managers/product designer.

Responsibilities

We're looking for a highly specialized AI Productivity & Enablement Lead to act as a force multiplier across our engineering organization. This pivotal role will be embedded with multiple engineering squads, driving the effective, efficient, and responsible adoption of Artificial Intelligence (AI) and Generative AI (GenAI) tools to significantly enhance software development speed, quality, and engineer satisfaction. You will be the expert on "AI as a tool," bridging the gap between cutting-edge AI capabilities and practical, high-leverage application in the daily coding workflow.

 

  • AI Tool Adoption and Integration:
    • Act as the primary champion and subject matter expert for developer-focused AI tools, including GitHub Copilot, Gemini (or similar code assistants), and intelligent IDEs (e.g., Cursor).
    • Strategize, pilot, and drive the seamless integration of these tools into existing CI/CD pipelines and engineering workflows
  • Best Practices and Coaching:
    • Develop and deliver hands-on workshops, one-on-one coaching, and comprehensive documentation on effective prompt engineering for software development tasks (code generation, debugging, documentation, etc.). 
    • Establish and evangelize good practices for reviewing, validating, and integrating AI-generated code to maintain code quality, security, and architectural standards.
  • Productivity Use-Case Development:
    • Identify, scope, and prototype high-impact AI use cases for engineering teams, focusing on writing and generating unit/integration tests, automating code review suggestions (leveraging AI agents), and transforming technical debt reduction
    • Define and track key metrics (e.g., time-to-completion for coding tasks, test coverage improvement, reduction in cognitive load) to measure the impact of AI adoption
  • Knowledge Leadership and Community Building:
    • Foster an internal "AI for Engineers" Community of Practice, sharing successes, lessons learned, and the latest advancements in developer-focused AI.
    • Stay abreast of the rapidly evolving GenAI landscape and translate new capabilities into actionable strategies for engineering productivity.
  • Governance and Responsible AI:
    • Collaborate with Legal and Security teams to ensure the use of AI tools adheres to intellectual property, data security, and responsible AI guidelines.

Qualifications

  • 5+ years of experience in software engineering, development enablement, or developer productivity roles.
  • Deep, hands-on experience using and coaching others on modern AI code generation tools (e.g., GitHub Copilot, Gemini, Amazon CodeWhisperer).
  • Expertise in prompt engineering specifically for software development use cases.
  • Strong understanding of modern software development life cycles (SDLC), Agile methodologies, and engineering best practices (e.g., unit testing, code review, CI/CD).
  • Exceptional communication and presentation skills, with the ability to clearly articulate complex AI concepts to both technical and non-technical audiences.

Nice to have

  • Experience in a consulting, technical training, or similar role focused on driving organizational change and new technology adoption.
  • Familiarity with leveraging LLMs or AI agents for advanced tasks like automated bug finding, refactoring, or code review summarization.
  • Proficiency in at least two major programming languages (e.g., GoLang, JavaScript/TypeScript (Vue 3), PHP?, Maybe we could include Kotlin or Swift there too).

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