AI Engineering Lead

AI Engineering Lead

We are seeking an experienced and visionary AI Engineering Lead to drive the development and deployment of AI-powered systems and platforms. This role blends deep technical expertise in AI/ML with leadership and strategic delivery capabilities. You will lead a team of AI engineers and collaborate with data scientists, product managers, and business stakeholders to build scalable,
- grade AI solutions that deliver measurable business impact.

Key Responsibilities

• Lead and grow a
  - performing AI engineering team.
• Define AI engineering strategy, architecture, and roadmap aligned with business goals.
• Champion best practices in MLOps, model governance, and responsible AI.
• Design and implement scalable AI systems including model training, deployment, monitoring, and lifecycle management.
• Translate prototypes into robust,
  - ready solutions in collaboration with data scientists.
• Maintain high standards of code quality, testing, and documentation.
• Build and maintain AI/ML platforms and tooling to accelerate experimentation and deployment.
• Oversee and evolve Azure Foundry / Databricks-based AI environments.
• Integrate AI capabilities into products via APIs, microservices, or embedded intelligence.
• Drive automation, observability, and performance optimization across AI pipelines.
• Work
  - functionally to identify and prioritize AI opportunities.
• Communicate complex technical concepts to
  - technical stakeholders.
• Stay current with emerging AI technologies and assess their business applicability.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• 7+ years in software engineering, with 3+ years in AI/ML engineering.
• Proven leadership experience in delivering AI solutions at scale.
• Strong Python skills and experience with frameworks like Tensor
  Flow, Py
  Torch, Hugging Face.
• Expertise in MLOps, CI/CD for ML, and
  - native AI architectures (Azure, AWS, GCP).
• Experience with Docker, Kubernetes, and ML workflow orchestration.
• Familiarity with agentic frameworks (e. g. , Lang
  Graph, Microsoft Semantic Kernel).
• Experience with API management and microservices architecture.

Preferred Qualifications

• Experience with LLMs, generative AI, or reinforcement learning.
• Knowledge of vector databases, RAG, and prompt engineering.
• Understanding of data privacy, model explainability, and ethical AI.
• Familiarity with communication protocols like MCP and Google’s A2A.
• Experience with frontend frameworks (React, Type
  Script).
• Contributions to
  - source AI projects or published research.

What We Offer

• Access to
  - edge AI tools and infrastructure.
• Opportunities to shape the future of AI in a
  - growing organisation.

Ready to make an impact?

Apply now to join a team that’s transforming data into action across one of the world’s most iconic brands.