Lead Cloud 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.

Our UK Benefits 

• 35 days leave (including bank holidays). 
• Private medical insurance.
• Enhanced parental and adoption leave. 
• Financial coaching + 5% pension match.
• 40 hours of paid learning and development.

 View our full list of UK benefits. 

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, our Lead Engineer - Cloud plays a pivotal role in supporting the success of our Cloud engineers, our clients, and internal projects. Working closely with clients, you are responsible for the successful delivery of client and internal projects by building professional relationships with key client stakeholders, challenging where appropriate. Use your technical expertise to provide best practice advice and processes within your project team and the wider capability.

As our client demands expand from traditional cloud migrations to AI enablement and platform engineering, you will lead the charge in building autonomous platforms, managing AI lifecycles, and enforcing strict cost governance across cloud estates. You are seen as a leader internally and externally, through your technical expertise, guidance, and professionalism, both on and off a client. Alongside delivering for your customers, you will also support and mentor a team of cloud engineers to encourage their growth. You will be setting the technical direction of the team alongside Cloud Leads and Senior Engineers.

Key responsibilities:

Consultancy & Advisory

• Growth Mindset: Apply a growth mindset to identify new revenue opportunities on client accounts, working alongside the commercial team to successfully land additional work.
• Pre-Sales Contribution: Lead and contribute to pre-sales activities, RFPs, and BIDs, accounting for up to 5% to 10% of the role. Engage with the commercial team to drive high-value Cloud and Data advisory roles.
• Ambassadorial Presence: Act as an ambassador for CreateFuture in the public space, attending events, speaking, blogging, or leveraging social media to support the growth of the Cloud capability.
• Hands-on: you are an experienced engineer and can be active with the cloud platform tools, software development and writing efficient code for clients.

Technical Leadership & Platform Support

• Technical Direction: Take responsibility for the technical direction and delivery of single or multiple client and internal project teams, acting as either a technical lead or a solo contributor.
• AI-Native Infrastructure: Architect and implement the core engineering infrastructure required to run AI workloads reliably, moving client architectures from static data lakes to dynamic Vector Databases and Retrieval-Augmented Generation (RAG) architectures.
• Agentic Development: Build production-grade Agentic Workflows and custom AI agents, utilising advanced toolsets to bridge the widening market implementation gap.
• Setting Development Best Practices: Define, promote, and establish best practice tools, security approaches, and common service patterns across the entire CreateFuture organisation. Ensure Infrastructure as Code (IaC) is the organisational default and challenge inefficient legacy processes.
• FinOps & Governance: Enforce strict automated security and cost controls, real-time cost-anomaly detection, and cost estimation into the Software Development Life Cycle (SDLC) as a standard. Understanding of OpenTelemetry or other telemetry approaches.
• Internal Platform Support: Assist the Capability Lead and architects in defining and delivering an internal collection of reusable components, reference architectures, and Proof of Concepts (PoCs). Supporting the internal IT function in helping other parts of the business use Cloud services.

Leading & Mentoring

• Culture & Collaboration: Lead by example, creating a culture of open, honest feedback, collaboration, ownership, and accountability.
• People Development: Create a psychologically safe environment for the team that enables them to grow by supporting their development journeys and career aspirations.
• Capability Growth: Work alongside the Capability Lead and Director of Cloud and Data to identify missing or inconsistent skills within the department, supporting team members through tiered certification journeys.
• Recruitment: Collaborate with Talent Acquisition through the recruitment process, including conducting interviews, candidate debriefs, and strategic decision-making to attract top talent.

Skills & Experience

Core Technical Capabilities

Candidates must demonstrate a hybrid skillset, balancing Software Engineering (30%), Platform/SRE (40%), and Data Engineering (30%), with a core focus on Security, Governance, and Cost Management.

• Cloud & Infrastructure (40%): Advanced Infrastructure as Code (IaC) via Terraform, advanced Kubernetes administration (clusters, nodes, pods), hardcore networking (VPC peering, Service Mesh, Zero Trust security), and solution architecture experience, with a cost-optimisation mindset.
• Software Engineering, Agentic & AI Development (30%): Solid software engineer principles (pipelines, toolsets, testing, linting, vulnerability scanning, etc.) Production-level experience with tools such as Amazon Bedrock, AWS AgentCore, Azure AI Studio, LangChain, and writing automation scripts or custom AI agents using node or python.
• Data Engineering (30%): Experience deploying and maintaining data orchestration toolsets (e.g., dbt, Apache Airflow), ETL/ELT methodologies, real-time streaming (e.g., AWS Kinesis, Apache Kafka), Vector databases, and RAG architectures.
• Observability & FinOps: Experience implementing modern observability tooling (OpenTelemetry) alongside automated cost-control systems (such as Karpenter, Infracost, OpenCost, or Cloud Custodian).

Domain & Sector Experience

• Regulated Industries: Experience working in highly regulated sectors such as Financial Services or iGaming is helpful, demonstrating an understanding of strict compliance, data privacy risks, and governance guardrails.
• Consulting: Proven background in a client-facing consulting capacity, managing stakeholders, handling commercial realities, and meeting strict SLAs, timescales, and budgets.

Preferred Knowledge-level & Certifications

• Certified Kubernetes Administrator (CKA).
• Multiple professional-level certifications (AWS Certified Solutions Architect - Professional or Azure Architect AZ-305.)
• Beneficial for AWS GenAI Developer Professional, AWS ML Engineer Associate, or Azure AI Engineer Associate.
• FinOps Certified Practitioner (FOCP).