Senior Cloud & AI Platform Engineer

Working at CreateFuture

CreateFuture is an AI-native consulting partner where people do work that matters and are supported to do it well. We work alongside organisations such as PayPal, adidas, NatWest, FanDuel and Money Saving Expert, building digital products and services that make a difference  while always putting people first.

We’re a team of creators. We write code, shape delivery, build go-to-market strategies, develop AI solutions and create the practices that support our people. We work side by side with our clients, challenging what’s not working and helping them to build the future. Our commitment to craft, quality, and culture has helped us scale to over 600 people in just a few years.

CreateFuture is a Great Place to Work-Certified™ company and has won Best Workplaces UK multiple years in a row.

Join us on our journey. Let’s create tomorrow, together, today.

About the role and team:

At CreateFuture, the Senior Cloud Engineer is a vital individual contributor and a technical driving force within our delivery teams. You will work closely with clients and delivery teams to bridge the implementation gap, assisting with architectural designs and transforming them into production systems using autonomous and AI-native platforms.

This role requires a modern, hybrid engineering approach, blending infrastructure mastery with software development and data engineering principles. You will act as a technical expert on projects, building trusted relationships with client stakeholders, establishing engineering best practices, and mentoring engineers within the Cloud capability. Furthermore, you will actively contribute to setting engineering standards that influence the whole CreateFuture organisation.

Technical Delivery & Implementation

• High-Quality Execution: Proactively contribute to project teams by providing technical guidance, resolving complex technical blockages, supporting migration efforts and writing high-quality, spec-driven code.
• Platform Engineering: Build and maintain independent, self-service developer platforms that allow engineering teams to spin up compliant, ephemeral environments automatically using GitOps workflows.
• AI & Agentic Infrastructure: Implement the data pipelines, workflow orchestrations, and specialised compute footprints needed to support enterprise AI applications, using technologies like AWS Bedrock and AWS AgentCore.
• Observability & Reliability: Build robust monitoring and observability pipelines to ensure the health, performance, and security of distributed cloud applications and AI models.
• FinOps Standards: Embed automated cost-estimation tools into the standard CI/CD deployment pipelines, ensuring auto-shutdown policies and resource optimisation are configured by default.

Consultancy & Client Alignment

• Client Advisory: Collaborate with diverse stakeholders, including tech leads, project managers, and enterprise architects, to ensure successful project delivery according to timelines and budgets.
• Commercial Growth: Have a growth mindset on projects, recognising potential operational bottlenecks or new requirements, and own communicating these throughout the team for new opportunities.
• Best Practice Champion: Establish best practice tools and processes within client environments, confidently challenging legacy ways of working where appropriate.

Capability & Leadership Support

• Mentoring: Support and mentor engineers within CreateFuture and our client teams, helping them navigate their learning and technical skill gaps.
• Community Contribution: Actively engage in the internal engineering communities, helping to build out an internal repository of reference architectures, Infrastructure as Code templates, and technical blogs.
• Culture and Feedback: Help foster an inclusive, collaborative, and psychologically safe team environment by providing timely, open, and honest technical feedback.

Core Technical Capabilities

Candidates must demonstrate a hybrid balance across the three strategic pillars: Software Engineering (30%), Infrastructure (40%), and Data Engineering (30%).

• Infrastructure & Automation (40%): Lots of experience in writing declarative Infrastructure as Code using Terraform, container orchestration with Kubernetes (managing clusters, nodes, and pods), and building CI/CD pipelines via GitHub Actions.
• Software & Agentic Engineering (30%): Proficiency with modern scripting languages for building custom AI agents, configuring workflow orchestration, connecting enterprise API integrations, and implementing agentic guardrails.
• Data Engineering (30%): Practical experience implementing components of data pipelines, including real-time streaming tools (AWS Kinesis, Kafka), data orchestration (dbt, Airflow), and managing Vector Databases for RAG architectures.
• Observability & Cost Management: SRE/Platform experience with the practical application of real-time monitoring and cloud cost optimisation using native CSP tools or utilities like Infracost and Karpenter.

Domain & Sector Experience

• Regulated Industries: Experience delivering secure platforms within highly regulated environments, such as iGaming, Financial Services, or banking, where Zero Trust security and strict compliance controls are mandatory, is highly advantageous.
• Consulting: Proven experience operating in a client-facing or consulting engineering role, demonstrating strong communication skills, relationship-building capabilities, and adaptability across changing technical contexts.

Preferred Knowledge-level & Certifications

• Associate-level cloud certifications (e.g., AWS Solutions Architect Associate or Azure AZ-104).
• At least 1 professional-level certification.
• Progressing toward or holding multiple professional certifications such as CKA (Certified Kubernetes Administrator), AWS ML Engineer Associate, or FinOps Certified Practitioner.