AI Engineering Lead

AI Engineering Lead

About Glue Reply:

Glue Reply is the outcome-focused Architecture specialist within the Reply Group. Through services encompassing Business Change/Transformation, Strategy & Architecture, Data exploitation and Integration, Glue Reply is able to help its clients succeed by turning strategy into tangible solutions and vision into practical outcomes. Glue Reply diagnoses the challenges and advises on the way to make real impact – enabling its clients to deliver. www.glue.reply.com  

Role Overview:

As an AI Engineering Lead, you will own the technical vision and oversee the engineering delivery of AI solutions for clients. You will be instrumental in establishing and scaling AI capabilities by defining standards, leading research and experimentation, and building reusable, production-grade systems. This role requires both strong technical leadership and hands-on involvement in architecture, coding, and deployment, empowering your team to deliver impactful solutions. The ideal candidate has a robust background in software and ML engineering, with a passion for agent-based systems, modern AI architectures, and real-world AI applications.

Responsibilities:

• Lead the design and implementation of advanced AI solutions, including LLMs, agentic systems, and retrieval-augmented pipelines.


• Design, deploy, and optimise scalable AI workloads on cloud platforms (AWS, GCP, Azure) for high performance and reliability.


• Define and enforce architectural standards, design patterns, and best practices for AI engineering.


• Build and optimise MLOps pipelines, CI/CD workflows, and infrastructure-as-code for production ML systems.


• Ensure reliability, observability, monitoring, and performance optimisation of deployed AI systems.


• Drive applied research and experimentation to explore and implement emerging AI architectures and techniques.


• Provide technical leadership, mentorship, and foster a collaborative culture within the AI engineering team.


• Build reusable components, frameworks, and internal tooling to enhance delivery speed and consistency.

About the Candidate:

• Minimum BSc (2.1 or higher) in Computer Science, Engineering, Mathematics, or related STEM field.


• 3+ years of hands-on software engineering experience (Python preferred), with a proven record of delivering production-grade AI/ML services.


• Practical experience designing and shipping LLM solutions using RAG/agentic patterns, orchestration frameworks (e.g., LangChain, LlamaIndex), vector search, and API integrations.


• Demonstrated ability to deploy and manage AI workloads on major cloud platforms (AWS, Azure, or GCP).


• Strong knowledge of DevOps/MLOps practices, including CI/CD, containerisation, and orchestration (Docker, Kubernetes).


• Experience leading and mentoring small-to-medium engineering teams, balancing technical delivery and team growth.


• Excellent problem-solving and system design skills, with expertise in architecting scalable, distributed AI systems.