This fast-growing business sits at the forefront of applied AI, working with major organisations to build and deploy intelligent systems that solve real operational challenges.

With a strong product roadmap and a collaborative culture, they offer the chance to work on high-impact projects in a fast-paced, forward-thinking engineering team.

This is a DevOps-centric, client-facing engineering role focused on getting AI systems—particularly agent-based solutions—successfully deployed into customer environments.

You’ll work across cloud, hybrid, and on-premise setups, navigating real-world constraints (networking, security, Kubernetes clusters, containerised workloads, etc.) and collaborating directly with clients to get solutions up and running.

You’ll work closely with senior engineering leadership to support deployments, contribute to agent-driven product builds, and ensure smooth delivery across varied technical landscapes.

Key attributes of the suitable DevOps Engineer (AI Deployment) include:

• Deployment & Delivery Experience – Hands-on experience deploying software or platforms into client environments (on-premise, hybrid or cloud).
• DevOps Foundations – Solid experience with Docker and Kubernetes (both essential), plus comfort working across different cloud providers and networking constraints.
• Interest in AI & Agents – Not a pure ML role—just curiosity or side projects involving AI agents, LLM tools, or automation frameworks.
• Client-Facing Mindset – Confidence working directly with customers, understanding their environments, and guiding them through deployment and solution delivery.
• Growth Mentality – 2+ years’ experience in DevOps, infrastructure, platform engineering or forward-deployed engineering roles.

This fast-growing business sits at the forefront of applied AI, working with major organisations to build and deploy intelligent systems that solve real operational challenges.

With a strong product roadmap and a collaborative culture, they offer the chance to work on high-impact projects in a fast-paced, forward-thinking engineering team.

This is a DevOps-leaning, client-facing engineering role focused on getting AI systems—particularly agent-based solutions—successfully deployed into customer environments.

You’ll work across cloud, hybrid, and on-premise setups, handling real-world constraints (networking, security, Kubernetes clusters, containerised workloads, etc.) and collaborating directly with clients to get solutions up and running.

You’ll work closely with senior engineering leadership to support deployments, contribute to agent-driven product builds, and ensure smooth delivery across varied technical landscapes.

Key attributes of the suitable AI Deployment Engineer:

• Deployment & Delivery Experience – Hands-on experience deploying software or platforms into client environments (on-premise, hybrid or cloud).
• DevOps Foundations – Solid experience with Docker and Kubernetes (both key), plus comfort navigating different cloud providers and networking constraints.
• Interest in AI & Agents – Not a pure ML role—just curiosity or side projects involving AI agents, LLM tools or automation frameworks.
• Client-Facing Mindset – Confidence working directly with customers, understanding their environments, and guiding them through deployment and solution delivery.
• Growth Mentality – 2+ years of experience in DevOps, infrastructure, platform engineering or forward-deployed engineering roles.

This pioneering organisation offers an advanced enterprise platform that delivers predictive analytics and AI-powered decision-making. Their digital AI agents provide always-on, intelligent insights — empowering top-tier clients across sectors such as asset management, banking, retail, etc. to dramatically enhance performance and efficiency.

As the Lead Solutions Engineer, you will bridge business needs with strong technical delivery — defining and documenting scalable architectures, leading engineering teams through execution, and ensuring high-quality outcomes for enterprise clients.

This hands-on leadership role combines strategic design with technical depth, translating complex requirements into actionable, well-structured solutions. You’ll collaborate closely with stakeholders, guide delivery teams, and continue to develop your expertise in modern AI systems, including LLMs, RAGs, and agentic workflows.

Key attributes of the suitable Lead Solutions Engineer include:

• Proven solution delivery expertise – experienced in leading full project lifecycles, from design through deployment, ensuring scalable, high-quality outcomes.
• Strong communicator and problem-solver – skilled at translating complex business requirements into structured, actionable solution architectures.
• Hands-on technical leadership – comfortable guiding engineering teams, engaging in system design discussions, and fostering collaboration across stakeholders.