AgenticAI Software Engineer

North Carolina, United StatesOnsiteTemporaryPosted 2 months agoVisa sponsorship available

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Role summary

We are seeking a skilled Software Engineer with a strong backend or systems background to build advanced agentic AI applications. This role requires proven experience in developing LLM-powered systems beyond prototypes, with a focus on designing and implementing agentic systems, including agents, workflows, MCP-based tool integration, and RAG. You will leverage your proficiency in Python and experience building production APIs to contribute to our developer platform. The ideal candidate will have a solid understanding of system observability, evaluation, operational ownership, and experience with Kubernetes design patterns, IaC, and CI/CD pipelines. This position offers the opportunity to work on cutting-edge AI technologies within a dynamic environment.

Required Experience

- 5+ years of professional software engineering experience, with a strong backend or systems background.
Proven experience building LLM-powered applications beyond prototypes.
Hands-on experience designing and implementing agentic systems, including agents, workflows, MCP-based tool integration, and RAG.
Strong proficiency in Python (or similar agent-oriented languages) and experience building production APIs or services.
Experience designing systems with observability, evaluation, and operational ownership in mind.

Domain / Problem Space

You will work on agentic systems in the context of:
- Experience with internal developer portals like Backstage with associated patterns like GitOps, API-driven microservices, paved paths, and more
Experience with design patterns in Kubernetes like controllers, control planes, operators, and more
Work on container orchestration, infrastructure as code (IaC), and CI/CD pipelines for deploying and managing k8s instances.
Monitor the performance of developer platform, identify potential issues, and ensure high availability of the platform.
Using Infrastructure As Code (IAC) best practices, create automated infrastructure within the cloud and on-premise platform, including package management, application load and configuration, and systems monitoring and administration.
Deliver improvements to source code management, deployment, operations, maintenance, cost control, security, monitoring, and audit tools and processes.
Implement and maintain CI/CD tools and processes to support development, QA, and customer value realization teams.
Manage a service critical codebase with version control using Git including Gitlab, or Github
These domains require agents that operate on real, evolving data, integrate deeply

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