AI Engineering Manager

Lead and scale a high-performing AI engineering team while driving end-to-end delivery of AI solutions from ideation through production deployment in the telecommunications sector.

Responsibilities

• Team Leadership & Development — Build, manage, and mentor a team of AI Engineers and researchers through hiring, onboarding, and regular 1:1s
• Foster technical excellence by documenting and championing engineering best practices
• Conduct daily/weekly/monthly delivery ceremonies including stand-ups and sprint planning

Strategic Delivery & Roadmap Ownership

• Co-own and execute the AI roadmap alongside the AI Solution Architect
• Manage the AI engineering backlog, prioritizing initiatives in collaboration with the Solution Architect
• Translate business requirements into actionable AI backlogs with product managers
• Own complete AI delivery lifecycle from concept to production deployment

Stakeholder Management & Governance

• Coordinate across organizational stakeholders including Data Governance, Security, and country business teams
• Manage delivery expectations by clearly defining experiments, rollouts, and solution iterations
• Ensure compliance with internal and external governance frameworks and regulations
• Advocate for AI trends and technological advancements relevant to telecommunications

Quality & Performance Management

• Maintain high standards in AI delivery and operations
• Track team progress and solution performance using relevant KPIs and metrics
• Adhere to AI development and delivery engineering lifecycle standards

Skills & Requirements

• Hands-on coding skills and active involvement in AI development
• Practical experience in AI operations and MLOps
• Knowledge of digital and data technologies including web/mobile applications and DataLake architectures

Leadership Excellence

• Proven track record in people management and delivery leadership

AI Project Experience

• Hands-on exposure to AI initiatives including GenAI, voice bots, AI agents, and similar technologies

Technical Foundation

• Solid understanding of software engineering fundamentals and principles

Business Acumen

• ROI-focused mindset for evaluating and delivering AI solutions

Cloud & AI Expertise

• Working knowledge of cloud platforms and familiarity with AI tools, frameworks, and concepts including LLMs, RAG, prompt engineering, and Python programming