AI Solutions Engineer 1

About the Role We're building AGS's AI Engineering team from the ground up, and we're hiring engineers at the start of their careers who want to build real AI systems—not tinker with demos. As a AI Solutions Engineer I, you'll write code that ships to production, contributing to intelligent agents, agentic workflows, and the reusable Foundation Layer capabilities that power them. This is a learning-intensive role with real responsibility. You'll pair with senior engineers and the Lead, participate in code reviews, and build working features from day one. We don't expect you to know LLMs or the Microsoft ecosystem yet—we expect strong software engineering fundamentals and the drive to learn fast. If you can write clean code, reason about problems clearly, and take feedback well, we'll invest in your growth. We hire engineers, not configuration specialists. If you want to write real software that solves real problems using AI, this is where to start. Responsibilities   Build & Deliver Develop features for intelligent agents, conversational interfaces, and agentic workflows Implement components of Foundation Layer services under guidance from senior engineers Write integrations between AI capabilities and enterprise systems (M365, Dataverse, external APIs) Write clean, tested code that follows team patterns and standards Fix bugs, investigate issues, and improve existing solutions   Learn & Grow Pair program with senior engineers and the Lead to learn architecture patterns and best practices Participate actively in code reviews—ask questions, give thoughtful feedback, and apply what you learn Build understanding of our technology stack: Semantic Kernel, Azure, Microsoft 365, LLMs Develop skills in prompt engineering, RAG patterns, and agent design through hands-on work Take on progressively more complex work as your skills develop   Engineering Practices Write unit and integration tests for your code Follow CI/CD practices and contribute to build and deployment processes Document your work—what you built, why, and how it works Monitor deployed solutions and participate in incident response   Collaboration Work with AI Solutions Analysts to understand requirements and ask clarifying questions Communicate progress, blockers, and what you're learning to your team Participate in sprint ceremonies and contribute to planning discussions Support QA by clarifying implementation details and fixing defects Qualifications   Required 1–3 years of software engineering experience (internships and personal projects count) Strong programming skills in Python and/or TypeScript Solid CS fundamentals: data structures, algorithms, and basic systems thinking Experience with Git and version control workflows Ability to write and run tests Clear communication skills—you can explain your code and your reasoning Intellectual curiosity and a bias toward learning by building   Preferred Experience building web applications or APIs (any framework) Familiarity with cloud platforms (Azure, AWS, or GCP) Exposure to AI/ML concepts, LLMs, or chatbot development Experience with CI/CD pipelines or containerization (Docker) Computer science degree or equivalent practical experience Familiarity with agile development practices   Technology Stack Languages: Python, TypeScript Platforms: Azure (Container Apps, Functions, AI Services), Microsoft 365 Agent Development: Copilot Studio, Power Automate, custom orchestration Data: REST APIs, Dataverse, SQL, Snowflake AI/ML: Large Language Models, prompt engineering, RAG patterns, MCP Tools: Git, GitHub, CI/CD pipelines, Docker   We don't expect you to know all of this. We expect the fundamentals and the ability to learn the rest quickly.   What We're NOT Looking For People who want to configure tools rather than write code Engineers who wait to be told exactly what to do and how to do it Developers who skip testing, documentation, or code review People who treat AI as a black box rather than something to understand   What Makes You Stand Out You've built something—a side project, an open-source contribution, a school project you're proud of You write code that's clean and readable, not just functional You ask good questions when you're stuck instead of spinning You take feedback as fuel, not criticism You're curious about how things work under the hood You want to be great at this, not just good enough   Career Growth   This is the entry point for our engineering career track: Junior → Senior → Lead → Architect You'll have a clear path forward with real mentorship. The Lead AI Solutions Engineer and senior engineers will invest in your development through pairing, code review, and progressively larger scope. Engineers who grow quickly here will take on ownership of features, then systems, then architecture. As a workplace, we focus on relationships – with each other, our clients and our candidates - in fact serving others is one of our core values. We support open communication and recognize that giving constructive criticism can be even harder than receiving it. We appreciate the fearless and the passionate, who force us to be better. Everything we do sits on a pillar of diversity - diverse perspectives, backgrounds and ideas drive innovation and make us successful. See what it’s like to work at AGS by searching #LifeAtAGS on any social network.