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Software Engineer - Cloud-Native Serverless & AI Tools

Job in Manchester, Greater Manchester, M9, England, UK
Listing for: Acceleraate Limited
Full Time position
Listed on 2026-06-04
Job specializations:
  • IT/Tech
    Cloud Computing, AI Engineer, Systems Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 GBP Yearly GBP 80000.00 100000.00 YEAR
Job Description & How to Apply Below

Salary dependent on experience + Benefits + Bonus

Role Overview

As a Software Engineer at Acceleraate, you will build across two fronts: the customer-facing platforms that deliver customer experience, and the internal tooling that powers our wider delivery team. The balance of that mix will shift over time, but the common thread is the same: well-architected, cloud-native software built on a serverless-first approach, where engineers take full ownership of what they deliver - from application code through to infrastructure.

Our AWS platform is well-established - CDK-managed, consistently structured across the estate, and set up to best practice from the ground up. We need someone who can operate at that standard, extend what we have thoughtfully, and bring genuine capability to new problems as they emerge.

You will work directly alongside our CTO and Engineering Director, both hands-on engineers. Decisions are made at engineering level. There is no lengthy approval chain between an idea and building it.

Why This Role is Exciting

Real breadth: You'll work across customer-facing products, integration platforms, and internal tooling - often within the same sprint.

Strong foundations to build on: Our AWS estate is serverless-first, CDK-managed, and built to best practice.

Integration at the core: We connect Zoom's ecosystem with third-party platforms for real enterprise clients. The integration problems here are genuinely interesting.

POC to production: We regularly evaluate new technologies to solve client problems. You'll be expected to pick things up, form a view, and prove it out.

AI as a real engineering tool: We use AI actively as part of how we engineer, and we expect you to do the same.

What You Will Be Doing Build and Extend Customer-Facing Platforms

A significant part of this role involves building and evolving the products our customers interact with directly. These are cloud-native, serverless applications - some greenfield, some established - and the work ranges from new feature development to architectural improvements as our customers' requirements grow.

You'll need to keep end users front of mind - the best technical decision and the right user experience don't always point in the same direction. Good engineering here means understanding the customer experience problem first, then building the right solution for it.

Design and Deliver Integrations

Integration is central to what Acceleraate does. You'll work with third-party APIs across a range of enterprise platforms - reviewing documentation, evaluating feasibility, and building robust integrations via our Integration Hub platform.

There's real design work involved here. You'll need to think about failure modes, understand data flows end to end, and make sure things behave sensibly and are recoverable when something unexpected happens.

Own Your Infrastructure

Infrastructure is a core part of the engineering work here - it's defined and managed alongside the application code using AWS CDK across the application estate.

Our wider AWS governance layer - account structure, security controls, audit logging, and compliance guardrails - is managed via Terraform and built to best practice from the outset. You won't be in the weeds of that day to day, but you'll understand why it exists and what it gives us.

You'll operate within a Git Hub Actions CI/CD pipeline and an NX-managed monorepo. Understanding build pipelines, dependency graphs, and deployment strategies is part of the role, as is improving them when they're slowing things down.

Evaluate New Technologies and Drive POCs

We regularly encounter problems where the right solution isn't obvious, or where a new technology might open up a better approach. You'll be expected to pick things up, build something to test your thinking, form a view, and communicate it clearly.

Engineering with AI

We use AI tooling across the engineering team - for writing and reviewing code, exploring approaches, debugging, and generally moving faster. We expect you to do the same. That means being genuinely curious about the tools, using them regularly, and having the judgement to know when the output is good, when it's subtly…

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