Team Lead, Core Efficiency Engineering & AI Enablement
We are seeking a Team Lead, to lead a team of engineers focused on improving the speed, quality, and effectiveness of our Production Support and Quality Engineering organizations. This role will drive the development of internal tools, automation, and AI-powered solutions that reduce manual effort, improve workflow efficiency, accelerate testing, strengthen operational support, and unlock smarter ways of working through the practical use of AI and LLM technologies.
This team is responsible for developing internal tools, workflow solutions, automation, and AI-enabled applications that help teams operate more efficiently, improve decision-making, and scale more effectively. The ideal candidate is a hands-on technical leader with strong product thinking, execution focus, and a sense of urgency, who can move quickly from idea to prototype to production-ready solution.
Key Responsibilities
- Lead and grow the Efficiency Engineering & AI Enablement team, setting direction, priorities, standards, and delivery expectations.
- Partner closely with Production Support and Quality Engineering leaders to identify inefficiencies, workflow bottlenecks, and opportunities for automation, tooling, and intelligent assistance.
- Design, build, and deliver internal applications and engineering solutions that improve productivity, operational consistency, visibility, and quality.
- Drive the practical use of AI and LLMs to improve engineering and operational workflows, with a focus on measurable impact and user adoption.
- Identify, prioritize, prototype, and scale high-value AI-enabled use cases such as knowledge assistants, incident analysis and triage support, issue summarization, test case generation, defect analysis, and engineering productivity tooling.
- Use rapid application development and rapid prototyping approaches to quickly turn ideas and operational pain points into usable internal tools.
- Build solutions that evolve from lightweight prototypes into scalable, maintainable, secure, and production-ready applications.
- Establish and manage a roadmap for efficiency and AI enablement initiatives based on business value, speed to impact, feasibility, and long-term strategic benefit.
- Define and track success metrics, including time saved, reduced manual effort, improved incident response, faster testing cycles, better knowledge accessibility, improved release quality, and higher operational efficiency.
- Coach and mentor team members while building a culture of flexibility, accountability, innovation, urgency, and continuous improvement.
Qualifications/Skills Required
- Proven experience leading engineering teams or technical delivery teams.
- Strong software engineering background building internal tools, workflow platforms, automation frameworks, or engineering productivity solutions.
- Demonstrated experience applying AI and LLM technologies to practical enterprise use cases, including intelligent automation, conversational tooling, and AI-assisted workflows.
- Strong experience across modern application, backend, and cloud technologies, including React, Next.js, Angular, Python, FastAPI, Java, Spring Boot, PostgreSQL, AWS, Docker, MTK, and open-source LLM libraries.
- Strong understanding of containerization and modern application delivery patterns, including building, packaging, deploying, and supporting containerized applications.
- Experience partnering with Production Support, DevOps, SRE, QA, test engineering, or release management teams.
- Track record of identifying high-value opportunities, moving quickly, and delivering practical, well-adopted solutions.
- Experience with rapid prototyping, iterative development, and turning ideas into scalable, production-ready tools.
- Strong communication, stakeholder management, prioritization, and delivery skills.
- Ability to balance speed, flexibility, and urgency with sound engineering judgment, long-term maintainability, and production quality.
- Experience with AI-powered productivity tools, operational tooling, CI/CD, observability, and high-reliability environments is a plus.
What Sets This Role Apart
This is not a traditional internal tools role. This position sits at the intersection of engineering productivity, operational excellence, software quality, and AI enablement. The right candidate will help define how modern engineering teams use AI and LLMs to work smarter, move faster, and operate more effectively. Success in this role will come from combining technical leadership with speed, flexibility, pragmatism, and a strong bias toward action. You should be equally comfortable discussing long-term strategy, rapidly prototyping a new idea, and leading a team that delivers practical solutions with real operational impact.
