Senior Software Engineer, Iris AI

As a Senior Software Engineer, you'll design, build, and operate the cloud services that drive Delinea's AI features. LLMs are a core part of your toolkit: from inference and retrieval to agents and evaluation, you’ll take ownership across the product surface. Our services are developed in C#/.NET, Python, and Go—strength in any is valued, and openness to learn others is expected.

Responsibilities

Build and operate scalable, highly available backend services in C#/.NET, Python, and Go, utilizing Azure and Kubernetes; Develop LLM-powered features using platforms such as Azure AI Foundry: model integration, context pipelines, RAG, tool calling, agents, and evaluation; Design event-driven, asynchronous architectures across microservices; Take end-to-end responsibility for delivery, including infrastructure-as-code with Terraform, CI/CD pipelines, monitoring, and production incident response; Collaborate with product, UX, and other platform teams; actively participate in code and design reviews; Leverage AI in your daily workflow; use coding agents to design, write, and review code held to the same standard as hand-written code.

Requirements

Bachelor’s in Computer Science or related field, or equivalent experience; 8+ years of experience designing and building production backend services in C#/.NET, Python, or Go, and engaging across the full software development lifecycle; Hands-on experience building products with LLMs, including inference, structured outputs, RAG, tool calling, or agents (e.g., Azure AI Foundry, OpenAI API, Amazon Bedrock, Google Vertex AI, Anthropic API, or similar); Proficiency with AI-assisted development (e.g., Claude Code, GitHub Copilot, Cursor), with emphasis on spec-driven development, careful context management, and verified, tested output; Strong understanding of distributed systems, API design, and microservices, as well as experience with a major cloud provider; Sound knowledge of multi-tenant SaaS architecture and the challenges of operating at scale.

Nice to have

Experience building tools, APIs, or integrations that AI agents call (e.g., MCP servers, function/tool-calling interfaces, plugins); Depth in ML and MLOps: fine-tuning, evaluation harnesses, and model deployment in production; Expertise in Kubernetes, Terraform, and CI/CD pipelines; Background in identity security, PAM, or Zero Trust architectures.

Benefits

competitive salaries; meaningful bonus program; healthcare insurance; pension/retirement matching; comprehensive life insurance; employee assistance program; time off plans; paid company holidays; meaningful work; culture of innovation; career progression