Senior Software Engineer - US

IRIS

About The Position

IRIS Software Group is hiring a hands-on Senior Software Engineer to solve complex problems and build scalable, cloud-based software. The role works across .NET, C#, cloud and web technologies to deliver secure and reliable products for large numbers of users. As IRIS develops its AI-first capabilities, the engineer will use AI-assisted engineering tools, contribute to modern cloud architecture and help shape engineering practices. The engineer will own significant product areas from initial design through production, including complex features and components. While the position has no direct reports, it involves technical influence through architectural contributions, technical discussions, mentoring and improving engineering standards. The role collaborates with Product, QA, Design, DevOps and other Engineering teams, and includes production support and troubleshooting.

Requirements

5 to 7 years of professional software development experience.
Strong backend development experience with .NET Core, C#, ASP.NET Core Web APIs and REST.
Experience with application architectures and distributed systems.
Strong knowledge of SQL, NoSQL and data architecture.
Experience with a modern frontend framework such as Angular, React, Vue.js or Blazor, or working knowledge of frontend development alongside deeper backend expertise.
Strong Azure or AWS experience in SaaS environments.
Experience with cloud services such as Azure Functions, Queues, Blob Storage and VMs, or AWS equivalents including Lambda, SQS/SNS and EC2.
Experience with Docker and/or Kubernetes; production-scale deployments using AKS or EKS are relevant.
Experience with Infrastructure as Code tools such as Terraform, Bicep, ARM Templates, AWS CloudFormation or CDK.
Strong understanding of CI/CD, deployment strategies and engineering automation.
Experience with automated testing and TDD/BDD practices.
Understanding of clean architecture, SOLID principles and domain-driven design.
Experience building highly scalable, internet-facing software.
Strong production troubleshooting skills, including application profiling, benchmarking and performance optimisation.
Knowledge of observability platforms such as DataDog, Application Insights or Amazon CloudWatch.
Good understanding of application security, vulnerability management and threat modelling.
Ability to take ownership of complex, multi-system solutions and lead technical initiatives.
Technical leadership through architecture decisions, mentoring and collaboration.
Strong communication skills, including explaining technical decisions to non-technical colleagues.
Ability to remain hands-on while influencing technical decisions; formal management experience is not required.

Nice To Haves

Experience in regulated or complex environments such as finance, health or government technology.
Experience with prompt engineering and Model Context Protocol (MCP) to connect AI systems with tools and services.
Advanced DataDog/APM, dashboards and alerting experience.
Experience with modern UI architecture such as micro-frontends, SSR or SSG.
Experience with security technologies and standards including OAuth2, OIDC and RBAC.
Experience with event-driven architectures.
Experience with GraphQL, SignalR or WebSockets.
Experience with DevOps automation and end-to-end ownership of software in production.
Advanced Azure or AWS certifications.

Responsibilities

Design and deliver complex, scalable systems, including high-traffic APIs, multi-service integrations and data-processing solutions.
Own large features and components end-to-end, from technical design and development through deployment and production support.
Build applications using C#, .NET Core, ASP.NET Core Web APIs and contemporary frontend technologies.
Influence architecture and technology decisions, balancing scalability, maintainability and business needs.
Build and improve cloud-native solutions across Azure or AWS.
Promote engineering practices including automated testing, TDD/BDD, CI/CD, observability, security and Infrastructure as Code.
Collaborate with Product, QA, Design, DevOps and other Engineering teams to translate requirements into software.
Lead technical discussions, story refinement and technical problem-solving.
Identify opportunities to reduce technical debt and improve existing systems.
Troubleshoot complex production and performance issues.
Mentor junior and mid-level engineers and support their technical development.
Help the team use AI-assisted engineering tools responsibly and effectively.
Contribute to architectural decisions and technical initiatives spanning multiple sprints or quarters.
Improve engineering standards and practices, and constructively influence technical decisions.