Senior .Net Developer 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. You’ll report to the Director of Engineering, Iris AI.

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.