Solutions Engineer (Early Career)
About Nerdio
At Nerdio, our mission is to simplify the lives of IT professionals and maximize their Microsoft cloud and end user computing investments.
We support organizations of all sizes looking to deploy, manage, and cost-optimize native Microsoft technologies. We partner with Enterprises and Managed Service Providers all over the world to add value on top of their existing native Microsoft investments like Azure Virtual Desktop (AVD), Windows 365, and Microsoft Intune.
Created in 2016, Nerdio has always taken a market-leading and collaborative approach to cloud deployment and management. In fact, our product roadmap is greatly influenced by the regular feedback we receive from having seen companies deploy AVD into production environments several thousand times using Nerdio technology.
Today, Nerdio is used in over 50 countries by more than 15,000 organizations of every size and vertical. We're committed to delivering exceptional service and support, which starts with identifying and supporting the best staff possible.
We are a fast-moving, nimble company looking for individuals who are collaborative, empathetic, driven and who love to move at the speed of light. If you want to be part of the AVD transformation that Microsoft and Nerdio are leading, then we want to speak with you.
About the role
The Corporate Development team is Nerdio's internal R&D and AI engineering hub. We build the automations, AI agents, AI-powered tools, and full-stack internal applications that make teams across Nerdio faster and more effective. The team also works closely with the data engineering function on the systems and data that power reporting, analytics, and AI-driven applications across the business.
As a Solutions Engineer on this team, you will be a hands-on builder working across an unusually broad range of technologies and business problems. You might spend one day building an AI agent, another adding a feature to an internal web application, another integrating with an API or MCP server, and another prototyping an idea for Sales, Support, Product, or Operations.
This is an early-career engineering role designed for someone who is curious, technically capable, comfortable learning quickly, and excited to use modern AI development tools as part of their everyday workflow. You are not expected to arrive knowing everything in our stack. You are expected to be able to learn quickly, ask good questions, understand what you are building, and steadily take on more ownership as your experience grows.
Our development process is heavily AI-assisted. Tools such as Claude Code, Cursor, Copilot, and other AI development environments are part of how we work every day. We care less about how quickly you can write code from scratch and more about whether you can understand a system, reason through a problem, evaluate AI-generated code, troubleshoot when something goes wrong, and ultimately take responsibility for what you ship.
What you'll do
Research, Development & Rapid Prototyping
- Work with the team to turn real business problems across Nerdio into prototypes, automations, and internal applications.
- Experiment with new AI models, APIs, frameworks, SDKs, and developer tools.
- Build proofs of concept quickly, gather feedback, and help determine which ideas are worth continuing.
- Learn how to move successful prototypes toward secure, maintainable production systems.
- Contribute ideas for new tools and automations based on problems you observe across the company.
AI Engineering & Automation
- Build AI-powered workflows, agents, and internal tools with guidance from more experienced engineers.
- Work with technologies such as tool/function calling, MCP, APIs, structured outputs, retrieval, agent orchestration, and LLM-driven automation.
- Integrate AI systems with internal business platforms and data sources.
- Test AI behavior, investigate failure modes, and improve reliability.
- Learn and apply the team's patterns for building AI systems safely and responsibly.
You do not need to already be an expert in agentic AI. You should be interested in understanding how these systems actually work beyond simply prompting a chatbot.
Full-Stack Development & Platform
- Build and maintain features across internal web applications.
- Work with technologies such as TypeScript, JavaScript, Node.js, React or similar frontend frameworks, and PostgreSQL.
- Build APIs, backend services, integrations, dashboards, and user-facing features.
- Debug issues across the application stack and learn how different parts of a production system interact.
- Participate in code reviews and learn how to evaluate both human-written and AI-generated code.
Our stack will continue to evolve. We value the ability to learn technologies quickly more than experience with one exact framework.
Azure, DevOps & Platform Engineering
- Deploy and operate applications in Microsoft Azure.
- Gain hands-on experience with services such as App Service, Container Apps, Functions, ACR, Key Vault, Entra ID, and Azure monitoring tools.
- Work with GitHub Actions and existing CI/CD pipelines.
- Learn good practices around environments, secrets, configuration, releases, and observability.
- Help diagnose deployment and production issues as they arise.
You are not expected to arrive as an Azure architect. You should be interested in learning how applications operate after the code leaves your laptop.
Data Analytics
- Work with data engineers and other team members to integrate applications with Nerdio's internal data platforms.
- Write queries and work with relational data used by dashboards, reporting, and AI applications.
- Help identify data quality issues and improve how applications consume and use internal data.
- Learn foundational data warehousing and data modeling concepts.
- Participate in projects that connect structured business data with AI-powered workflows.
AI Assisted Engineering
AI development tools are a core part of how this team works.
You will learn how to use tools such as Claude Code, Cursor, Copilot, and agent-based development workflows to research, design, build, test, and troubleshoot software. Using AI to write code is expected. Blindly accepting what AI produces is not.
You should develop the ability to:
- Explain what the code you are shipping does.
- Understand the architecture of the systems you work on.
- Identify when AI-generated code is incorrect, insecure, unnecessarily complicated, or solving the wrong problem.
- Break large problems into smaller tasks that AI systems can execute effectively.
- Validate results through testing, debugging, documentation, and experimentation.
- Know when AI is useful and when a simpler approach is better.
Collaboration and Internal Enablement
- Work directly with teams across Nerdio including Sales, Customer Success, Support, Product, Engineering, Operations, Finance, and Security.
- Help understand business problems before jumping directly into technical solutions.
- Demonstrate tools and features you have worked on to internal users.
- Gather feedback and turn it into product improvements.
- Share useful discoveries, development techniques, and AI workflows with teammates.
- Contribute to documentation and internal knowledge sharing.
As you grow in the role, you will have opportunities to lead demonstrations, own projects, teach others, and help shape how Nerdio uses AI and automation.
Security Awareness
- Learn and follow good practices around identity, authentication, secrets, permissions, data handling, dependencies, and application security.
- Consider security when designing and implementing features rather than treating it as something added afterward.
- Work with Nerdio's security team when deeper expertise or review is required.
Security is everyone's responsibility, but this is not primarily a security engineering role.
Required Qualifications
We are intentionally keeping the experience requirements broad. Strong recent graduates and early-career engineers are encouraged to apply.
- Bachelor's degree in Computer Science, Information Technology, Engineering, Cybersecurity, Data Science, or a related technical field, or equivalent hands-on technical experience.
- Demonstrated ability to build software through coursework, internships, personal projects, open-source contributions, employment, or similar experience.
- Working knowledge of at least one modern programming language. Experience with JavaScript or TypeScript is especially useful.
- Basic understanding of APIs, databases, web applications, and software development fundamentals.
- Familiarity with Git and source control concepts.
- Experience using modern AI tools for technical work, or a strong interest in learning AI-assisted software development.
- Ability to read code, reason about what it is doing, and troubleshoot problems.
- Strong curiosity and willingness to learn unfamiliar technologies.
- Ability to communicate technical ideas clearly and work collaboratively with others.
- Comfortable taking feedback, asking questions, and iterating quickly.
Preferred Qualifications
These are helpful, but we do not expect an early-career candidate to have all of them.
- Internship, coursework, or project experience building web applications.
- Experience with TypeScript, JavaScript, Python, PowerShell, or Bash.
- Experience with React, Node.js, or similar frameworks.
- Exposure to Microsoft Azure or another major cloud platform.
- Experience building something using an LLM API or AI SDK.
- Familiarity with AI concepts such as RAG, agents, tool calling, MCP, embeddings, or structured outputs.
- Experience working with relational databases or SQL.
- Familiarity with Docker, CI/CD, GitHub Actions, or Infrastructure-as-Code.
- Exposure to Microsoft technologies such as Entra ID, Microsoft Graph, Azure Virtual Desktop, Windows 365, or Intune.
- Personal projects that demonstrate experimentation, curiosity, or creative use of technology.
A strong GitHub project, internship, hackathon project, or independently built application can be just as interesting to us as professional experience.
KEY COMPETENCIES
- Learning Velocity: You can get dropped into something unfamiliar, research it, experiment with it, and become productive quickly.
- Builder's Mindset: You like making things work. You would rather build a small prototype and learn from it than spend weeks theorizing about the perfect solution.
- AI Fluency: You are comfortable collaborating with AI tools and interested in learning how to use them as engineering systems rather than simply chat interfaces.
- Technical Curiosity: You want to understand why something works, not just copy the solution that made the error disappear.
- Ownership: When you work on something, you care whether it actually works for the person using it.
- Pragmatism: You are willing to use the simplest technology that solves the problem instead of reaching for complexity because it is interesting.
- Communication: You can explain what you built, why you built it, and what you learned to both technical and non-technical colleagues.
- Adaptability: The technologies this team uses will change quickly. You are comfortable learning continuously rather than defining yourself by one language or framework.
WHAT SUCCESS LOOKS LIKE IN THE FIRST 12 MONTHS
3 Months
You understand the team's core applications, development workflow, Azure environment, GitHub practices, and AI development tooling. You are regularly contributing code, fixing issues, building smaller features, and participating effectively in the team's AI-assisted development process.
6 Months
You have shipped meaningful features, automations, or AI-powered capabilities into production and can independently handle well-scoped engineering tasks from development through deployment. You understand enough of the team's architecture to troubleshoot across multiple parts of the stack rather than only working within a single component.
9 Months
You can take a moderately scoped internal problem, work with the people experiencing it, design an appropriate solution, build a prototype, incorporate feedback, and move it toward production with limited guidance. You are beginning to develop deeper expertise in one or more areas such as AI engineering, application development, cloud infrastructure, data, or platform engineering.
12 Months
You are a trusted, independent contributor who can own meaningful projects end-to-end. You have shipped tools that people across Nerdio actively use, understand how those systems operate in production, and can explain the technical decisions behind them. You are increasingly contributing your own ideas, helping newer team members where appropriate, and developing toward broader technical ownership within the team.
Working Arrangement
This role is remote-first and works closely with teams across Engineering, Product, Data, Security, Sales.
This role is limited to US Persons or those with valid work authorization that does not require sponsorship.
Benefits and Incentives
- Competitive Base and Incentive Plan
- Stock Options
- Health and Welfare Plans*
- Life and Disability Plans*
- Retirement Plan*
- Unlimited Flexible Paid Time Off, including your birthday off!
- Collaborative Team Culture
- Benefits for international employees, outside the US, vary by country.
Nerdio is committed to a diverse and inclusive workplace. Nerdio is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
Pay: 60,000 - 70,000 USD per year
Location: Remote (United States)