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Selected role

Senior AI Engineer (Amazon Bedrock)

CreateFuture Manchester, ENG, GB

Senior Full-time

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:

A hands-on senior AI engineer embedded in client delivery teams, responsible for designing, building, and operating production-grade agentic AI systems on AWS. This role sits at the intersection of AI engineering and cloud architecture, owning the end-to-end implementation of multi-agent pipelines, knowledge bases, and orchestration frameworks using Amazon Bedrock and its surrounding ecosystem. The right candidate has shipped real AI agents to production — not just prototypes — and brings the rigour of a software engineer to a space that often lacks it.

Key Responsibilities

Design and implement production agentic AI systems on Amazon Bedrock, including multi-agent orchestration, memory management, and tool integration using Amazon Bedrock AgentCore and Strands Agents
Build, integrate, and maintain MCP (Model Context Protocol) servers that expose capabilities to AI agents across client platforms
Architect and implement RAG pipelines using Amazon Bedrock Knowledge Bases, managing vector stores, embeddings, and document ingestion from S3 and other sources
Apply the A2A (Agent-to-Agent) protocol to enable interoperability between agents across systems and workflows
Instrument AI systems with observability and tracing tooling — CloudWatch, spans, and traces — to support debugging, performance monitoring, and compliance requirements
Integrate LLMs into client applications through prompt engineering, context management, and function/tool calling patterns
Leverage serverless infrastructure — AWS Lambda, DynamoDB, S3 — to build scalable, cost-efficient backends for AI workloads
Collaborate with client engineering and product teams to translate requirements into agent architectures, contributing to technical roadmaps and AI strategy

Skills & Experience

Amazon Bedrock at scale — hands-on implementation of agents, knowledge bases, and model inference in production environments, not limited to basic API calls
Agentic AI and multi-agent systems — direct experience designing and deploying agent pipelines with real orchestration complexity
MCP (Model Context Protocol) — built or integrated MCP servers in a production or near-production context
Strands Agents — familiarity with the framework and its application to agentic workflows on AWS
RAG implementation — knowledge base design, chunking strategy, vector store configuration, and retrieval evaluation
Python — strong, applied proficiency in an AWS and AI context
AWS infrastructure — working knowledge of Lambda, DynamoDB, and S3 as components of AI system backends
Observability — experience instrumenting AI systems with tracing, logging, and monitoring tooling (CloudWatch preferred)
LLM integration — prompt engineering, tool/function calling, context window management, and output parsing
AWS certifications desirable, particularly the AI/ML Specialty

What we'll offer you:

We trust people to do their best work. That means flexibility over rigid rules, impact over activity, and real investment in your growth both professionally and personally. You'll be part of a supportive, and friendly culture, surrounded by smart, curious people who care deeply about what they do.

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

Depending on the role, we might also ask you to do a short presentation, a practical or technical task or have a values focused conversation. We will explain what is involved before anything happens.

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!

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