Software Engineer

SolarWinds Product and Engineering is building shared platform capabilities that help software teams use AI agents throughout the software development lifecycle. As a Software Engineer on the AI Development Platform team, you will build and improve the services, integrations, and developer workflows that make those capabilities useful, secure, and dependable.

You will contribute production-quality software for agent-based development workflows, including agent harnesses, execution and orchestration, custom tool integrations, and the supporting evaluation, testing, and telemetry. You’ll work with product and engineering partners to turn well-defined needs into working features, use AI tools as part of your own development workflow, and learn the platform’s production environment with support from senior engineers.

• Design, implement, test, debug, and maintain small-to-medium platform features and services.
• Build and improve agent-based software development workflows that take work from specifications and context through agent-assisted implementation, pull requests, review, and verification, including the harnesses, tools, and integrations that help agents plan and execute work, use engineering context, and produce reviewable results.
• Contribute agent orchestration and execution capabilities, including reliable, isolated environments with appropriate access to repositories, tools, and dependencies.
• Build and maintain custom MCP servers or similar integrations that connect agents to engineering systems such as source control, work tracking, documentation, CI/CD, and testing tools.
• Build and maintain testing and evaluation approaches for agents and models, including repeatable test suites, evaluation datasets or scenarios, regression checks, and observability to verify outputs and improve reliability.
• Contribute to platform capabilities for model and tool flexibility, usage attribution, budget visibility, and operational telemetry.
• Apply secure engineering practices, including least-privilege access, protection of secrets, useful auditability, and human review or approval where appropriate.
• Participate in code reviews and design discussions.
• Use AI development tools thoughtfully to improve productivity and code quality, while validating generated code and sharing useful practices with teammates.
• Write and maintain clear technical documentation, tests, scripts, and developer-facing guidance that make platform capabilities easier to adopt.

• Experience building and supporting software in a team environment, with sound skills in coding, debugging, testing, and version control.
• Ability to implement medium-complexity changes using established patterns, data structures, and engineering practices; willingness to ask for guidance when problems or risks exceed your experience.
• Familiarity with Git-based workflows, code review, automated testing, and iterative delivery.
• Practical problem-solving skills: you can clarify requirements, compare straightforward implementation options, and produce simple, effective solutions.
• Interest in cloud services, developer platforms, automation, and improving the software development experience for other engineers.
• Hands-on experience building with AI agents or agentic workflows, or developing the harnesses and integrations that enable agents to perform useful work. You can explain how you tested agent behavior and handled failures or uncertain outputs.
• Regular use of AI-assisted development tools, with the judgment to review, test, and take responsibility for the results.
• Clear communication and the ability to collaborate with engineers and partners across disciplines.

• Working with containers, isolated or sandboxed workloads, event-driven systems, or workflow orchestration.
• Building agent or model evaluation systems, testing frameworks, evaluation datasets, test fixtures, guardrails, or observability to assess quality, consistency, and reliability across changes.
• Working with LLM APIs, model gateways, usage telemetry, or cost controls.
• Experience with observability, identity and access controls, or secure software delivery.

At this level, you independently deliver scoped features and small-to-medium projects, while seeking senior-engineer input on design tradeoffs, unfamiliar production systems, and higher-risk changes. You contribute to team quality through testing, code review, documentation, and reliable follow-through; you are developing deeper knowledge of the platform stack and its production environment.