Forward Deployed Engineer - #2189454

Forward Deployed Engineer - Cloud

Salary: £110,000 – £130,000 + Bonus

Location: Liverpool based with hybrid working

The Opportunity

A leading global technology services and consulting organisation is looking for an experienced Forward Deployed Engineer – Cloud to join its growing Cloud and AI Engineering practice. This is a senior technical opportunity focused on delivering complex cloud platform modernisation and building the infrastructure that enables next-generation Generative AI and Agentic AI solutions. Working directly with enterprise clients, you'll take ownership of end-to-end technical delivery, translating business challenges into scalable cloud architectures and production-ready platforms. You'll operate at the intersection of Cloud Architecture, Platform Engineering, DevOps, Infrastructure Automation and AI, working alongside specialist AI engineers to ensure platform infrastructure and intelligent systems are designed and delivered together.

The Role

As a Forward Deployed Engineer, you'll lead the architecture, engineering and implementation of modern cloud platforms across Azure, AWS and GCP. You'll take responsibility for the full delivery lifecycle, from defining target-state architectures and building secure cloud foundations through to implementing automation, container platforms and production environments for AI workloads.

This is a hands-on position requiring strong technical depth, architectural judgement and the ability to engage directly with clients. You'll have significant autonomy to shape solutions, influence engineering standards and feed practical delivery experience back into the organisation's wider platform capabilities.

Key Responsibilities

• Lead the design and implementation of enterprise cloud platforms across Azure, AWS and Google Cloud.
• Translate complex business and technology requirements into scalable target-state cloud architectures.
• Build and operate enterprise Kubernetes platforms, including container orchestration and GitOps-based deployment using ArgoCD.
• Develop secure cloud landing zones and self-service developer environments.
• Engineer the infrastructure required to host and operate Generative AI and Agentic AI solutions, including LLM hosting, gateways and agentic workflows.
• Own end-to-end platform delivery, developing CI/CD pipelines and automated infrastructure using Terraform, Helm and Infrastructure as Code.
• Support legacy application transformation, including containerisation, microservices migration and API integration.
• Embed security throughout the engineering lifecycle, integrating security tooling into CI/CD pipelines and implementing Kubernetes namespace segmentation, managed identities and secure cloud access.
• Design and manage secure network connectivity, including SSL/TLS certificates, DNS zones and protected access to platform endpoints.
• Establish architectural standards, engineering guardrails and security controls using policy-as-code, OPA, secrets management and compliance-driven engineering.
• Implement full-stack observability using tools such as Grafana, Prometheus and OpenTelemetry.
• Work alongside AI engineers to ensure cloud infrastructure and AI delivery workstreams remain aligned.
• Capture technical insights and delivery lessons, using them to improve reusable platform frameworks and engineering standards.
• Contribute code, automated blueprints and technical feedback to central platform engineering teams.
• Act as a trusted technical advisor, helping clients make informed decisions around cloud strategy and platform modernisation.

Skills & Experience

• Extensive experience in solution architecture, platform engineering or cloud architecture, ideally within a client-facing consulting or enterprise environment.
• Strong hands-on experience across Azure, AWS and/or GCP, including cloud landing zones, networking, IAM and cost management.
• Production-level experience with Kubernetes, ArgoCD, GitOps and container platforms.
• Strong Infrastructure as Code experience, particularly Terraform and Helm.
• Proven ability to implement end-to-end platform security, including CI/CD security tooling, Kubernetes identity management, namespace segmentation and cloud access controls.
• Practical experience managing SSL/TLS certificates, DNS administration and secure network connectivity.
• Strong understanding of CI/CD pipelines, Git, GitHub and modern software delivery practices.
• Experience with microservices architecture, APIs and application modernisation.
• Knowledge of observability platforms, particularly Grafana, Prometheus and OpenTelemetry.
• Working knowledge of Generative AI infrastructure, including LLM hosting, LLM gateways and production AI deployment.
• Exposure to LLMOps and MLOps practices, including deploying, monitoring and managing AI systems in production.

Desirable Experience

• Exposure to Agentic AI frameworks such as LangGraph, CrewAI, AutoGen or Semantic Kernel.
• Understanding of LLM governance, including data privacy, responsible AI, guardrails and security controls.
• Experience leading legacy application modernisation, containerisation and microservices re-platforming.
• Experience defining enterprise platform standards, architectural guardrails and risk frameworks.
• A broad understanding of enterprise IT, alongside deep technical expertise in cloud and platform engineering.
• Previous experience advising senior client stakeholders and translating business requirements into technical roadmaps.
• Degree in Computer Science, Software Engineering, IT or a related discipline, or equivalent professional experience.
• Flexibility to travel and work at client sites when required.

What's on Offer

• £110,000 – £130,000 base salary
• Bonus
• Opportunity to work at the forefront of Generative AI and Agentic AI infrastructure.
• Exposure to major enterprise cloud transformation programmes.
• Hands-on involvement in designing and delivering modern cloud-native platforms.
• Access to technical training and certifications across Microsoft, Google and AWS.
• Personalised career development, coaching and mentoring.
• Opportunity to influence platform engineering standards and reusable technology frameworks.
• Hybrid working and a flexible working environment.
• A collaborative culture focused on technical innovation, continuous learning and career progression.