Requirements
- Strong experience as a Senior Software Engineer working across multiple technology stacks
- Proven DevOps experience, with a strong automation-first engineering mindset
- Experience designing, deploying and supporting production systems using CI/CD pipelines and infrastructure as code
- Ability to rapidly learn new technologies and apply them effectively in customer environments
- Excellent problem-solving and troubleshooting skills across software, infrastructure and cloud platforms
- Strong written and verbal communication skills, including confidence in customer-facing roles
- Hands-on experience with:
- Infrastructure as Code (Terraform, Ansible or similar)
- CI/CD pipelines and DevOps tooling
- C# (.NET 8+) and/or Java (Spring)
- JavaScript using a modern framework (React, Angular or similar)
- Bash and PowerShell
- AWS, ideally including Amazon Connect
- Containerisation and orchestration (Docker, Kubernetes)
- Linux environments
- (Desirable) Experience with relational databases such as MSSQL
- (Desirable) Experience with Redis or similar caching technologies
- (Desirable) Exposure to Azure
- (Desirable) Exposure to Google Cloud Platform (GCP)
- (Desirable) Experience with Go
- (Desirable) Experience with VMware
- (Desirable) Telephony or IVR experience
What the job involves
- As a Senior Software Engineer within the AI Practice, you will play a key hands‑on role in designing, building and operating secure, scalable and highly automated software solutions for our customers
- You will bring a strong DevOps mindset, taking ownership of solutions across the full lifecycle — from design and build through deployment, monitoring and continuous improvement
- The role is customer‑facing and delivery‑focused, working on AI‑enabled and cloud‑native solutions using modern, automation‑first engineering practices
- Reporting To Chris Nickson
- Design, build and maintain high‑quality software solutions using modern programming languages, cloud platforms and DevOps tooling
- Apply a DevOps and automation‑first approach across infrastructure provisioning, CI/CD, deployment, testing and operations
- Engineer secure, scalable and observable systems using modern DevOps practices, including infrastructure as code and automated quality controls
- Take ownership of services in production, including monitoring, troubleshooting, performance tuning and reliability improvements
- Work directly with customers to understand requirements, shape technical solutions and clearly communicate progress, risks and outcomes
- Troubleshoot complex issues across application code, integrations, infrastructure and cloud services
- Contribute to shared DevOps tooling, reusable components, infrastructure‑as‑code patterns and engineering standards within the AI Practice
- Collaborate closely with other engineers and delivery leads to ensure high‑quality, on‑time delivery
- Continuously evaluate and adopt new DevOps tools, technologies and patterns to improve delivery efficiency and platform reliability
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