AI Platform Engineer
Indexed description
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.
Join us on our journey. Let’s create tomorrow, together, today.
About The Role And Team
We're assembling a delivery team for a major AI platform programme with a client in a high-traffic, heavily regulated consumer sector. Like a lot of large engineering organisations, they have plenty of AI experiments and no shared foundation underneath them. Our job is to give them one. It needs to be a platform their product teams build on by default, with the governance and cost control a regulated business requires.
The platform has three moving parts, and you'll work across them rather than sitting in one lane.
- The inference control plane. The gateway and routing layer in front of Anthropic, AWS Bedrock, OpenAI and others, plus the failover behaviour that decides what happens when a
- Orchestration and capability lifecycle. The tooling that lets teams register, discover and reuse AI capabilities and agents, so the tenth team to need retrieval doesn't build it from
- Trust, safety and governance. The access controls, audit trail and cost attribution that make the platform defensible to a risk function.
on the team.
What You'll Be Doing
Technical Delivery & Implementation
- Gateway and routing: Build, run and evolve the API gateway and routing layer that connects engineering teams to multiple LLM providers, including the failover and load-shedding behaviour under provider degradation.
- Capability lifecycle: Design and build the orchestration and registration tooling behind a reusable capability marketplace, along with the API design, versioning and promotion
- Access and secrets: Implement RBAC and OIDC-based access control, and bring real discipline to API key issuance, rotation and revocation.
- Cost and latency: Build caching layers, routing economics and per-team cost attribution. Instrument adoption too, so the client can see which capabilities are earning their keep and
- Governance by design: Treat auditability, guardrails and safe defaults as part of the build rather than a later hardening pass, so agents running on the platform can be evidenced to a
- Engineering standards: Work to a high bar on testing, observability and documentation. Where behaviour is non-deterministic, treat evals, golden datasets, structured outputs and
Client Delivery & Stakeholder Management
- Working relationships: Build credibility quickly with the client's platform engineers, architects and engineering leaders, and hold your position with evidence when you think an
- Framing decisions: Explain the cost, risk and delivery trade-offs behind platform decisions in terms the client's business can act on and make pragmatic calls when technical ideals
- Delivery ownership: Plan and prioritise your own stream, estimate your work accurately, manage shifting requirements without dropping quality, and raise risks to timelines early.
- Working in the open: Contribute to discovery, scoping and estimation sessions, and flag missing or contradictory requirements before they become rework.
- Fitting in fast: Work within the client's existing standards, tooling and ways of working where they're sound, and make the case for change where they aren't.
- Documentation as you go: Leave architecture decision records, runbooks and API documentation that the client's own engineers can work from without you in the room.
- Knowledge transfer: Bring the client's engineers along as you build, through code review and pairing, so the platform is theirs to run at the end of the engagement.
- Exit readiness: Treat a clean handover as part of the definition of done from the first sprint, not something arranged in the final fortnight.
- Languages: Strong production Python or Go. We mean services you've owned, operated and had to debug under pressure, rather than scripts.
- API gateways: Production experience running a gateway at scale. Kong is our preference. Envoy or Apigee are equally welcome.
- Multi-provider LLM integration: Real integration work across more than one provider (Anthropic, AWS Bedrock, OpenAI or comparable), including the routing and failover design behind it.
- Identity and access: RBAC and OIDC in anger, plus credible API key lifecycle management.
- Platform fundamentals: Cloud infrastructure on AWS, infrastructure as code with Terraform, containers, CI/CD, and observability you built rather than inherited.
- Cost and performance: Caching strategies, latency budgets and cost optimisation for inference workloads.
- Registry patterns: Familiarity with MCP or comparable service-registry and tool-discovery
Expectations scale with level. At mid-level we're looking for solid, reliable delivery. At senior, ownership of a component and the judgement to set its standards. At principal, the architectural authority to set direction for the whole platform and the credibility to defend it in front of a client's stakeholders.
Domain & Sector Experience
- Regulated industries: Experience delivering in iGaming, financial services or another tightly regulated sector, where audit, data privacy and compliance guardrails are non-negotiable, is
- Scale: Comfort with high-throughput, latency-sensitive production systems.
- Contract and consulting delivery: A track record of landing in an unfamiliar codebase and organisation and being productive quickly. This engagement rewards people who can read a
Useful credentials
Track record matters more than certification here, but the following are useful evidence of depth:
- AWS certification at associate level or above, particularly Solutions Architect or DevOps Engineer Professional.
- Terraform Associate.
- AWS Certified Machine Learning or GenAI-track certifications.
We offer flexible working, including hybrid and remote options. Our office hubs are located in Edinburgh, Leeds, Manchester, London and Bulgaria, with occasional travel to client sites or CreateFuture offices when needed.
We trust you to manage your time balancing collaboration with client time and focused work. What matters is the impact you have, not how busy you look.
Our hiring process
We try to keep our hiring process clear, fair and respectful of your time. We aim to get back to everyone who applies and we will be upfront about where you are in the process.
It Usually Looks Like This
- Call with our Talent Acquisition Team
- Role specific capability interview
Inclusion at CreateFuture
We believe diverse teams build better workplaces and better products. We want CreateFuture to be a place where people feel able to be themselves and do their best work.
If you need any adjustments or support during the application process, just. We will do what we can to help.
We look forward to your application!
Create a free Caio profile to unlock more results and save your role and location preferences.
Unlock free search