Senior .NET/C# Engineer - Iris AI

You'll design, build, and run the cloud services behind Delinea's AI features, with LLMs as part of your toolkit: inference, retrieval, agents, and evaluation are all product surface you own. Our services are written in C#/.NET, Python, and Go. Be strong in one, and be willing to work in any. You'll report to the Director of Engineering, Iris AI.

Responsibilities

Build and run scalable, highly available backend services in C#/.NET, Python, and Go on Azure and Kubernetes; Build LLM-powered features on platforms like Azure AI Foundry: model integration, context pipelines, RAG, tool calling, agents, and evals; Design event-driven, asynchronous architectures across our microservices; Own delivery end to end: Terraform, CI/CD, monitoring, and production incident response; Work closely with product, UX, and other platform teams; give and get sharp code and design reviews; Build with AI every day. We use coding agents to design, write, and review code, and we hold that code to the same bar as anything written by hand

Requirements

A degree in Computer Science or a related field, or equivalent experience; 8+ years designing and building production backend services in C#/.NET, Python, or Go, with experience across the full software development lifecycle; Hands-on experience building products with LLMs (not just using them): inference, structured outputs, RAG, tool calling, or agents on Azure AI Foundry, the OpenAI API, Amazon Bedrock, Google Vertex AI, the Anthropic API, or similar; Fluency with AI-assisted development (Claude Code, GitHub Copilot, Cursor) treated as a discipline in its own right: spec-driven development, careful context, and verified, tested output; Strong grasp of distributed systems, API design, and microservices, plus experience with a major cloud provider; Solid understanding of multi-tenant SaaS architecture and the trade-offs of operating at scale; Must not require US work authorization now or in the future

Nice to have

Experience building tools, APIs, or integrations that AI agents call - MCP servers, function/tool-calling interfaces, plugins, or similar; ML and MLOps depth: fine-tuning, eval harnesses, and deploying and evaluating models in production; Kubernetes, Terraform, and CI/CD pipelines; Identity security, PAM, or Zero Trust background

Benefits

competitive salaries; meaningful bonus program; excellent benefits; healthcare insurance; pension/retirement matching; comprehensive life insurance; employee assistance program; time off plans; paid company holidays