AI Engineer

Systems Engineering Inc•Portland, ME

2d•Hybrid

About The Position

Systems Engineering is building out its AI practice, and we're looking for a talented, pragmatic AI Engineer to design and deploy real-world AI solutions for our clients. This isn't a research role — it's a builder role. You'll be developing AI agents, integrating LLMs, architecting data strategies, and deploying cloud-based AI systems that solve actual business problems for actual clients. You'll work hand-in-hand with our AI Solutions Consultant, taking business requirements and translating them into production-grade systems that people use every day. If you're excited by the pace of AI development and want to do meaningful, applied work, this is the role.

Requirements

Bachelor’s degree in business, Information Systems, Computer Science, Data Analytics, Engineering, or a related field; relevant experience may be considered in lieu of formal education.
3+ years of software or AI/ML engineering experience with real production deployments.
Experience with Microsoft AI platforms, including Copilot for Microsoft 365, Azure OpenAI, or Azure AI Foundry, and their application in business environments.
Proficiency in Python and API/systems integration development.
Cloud platform experience.
Strong grasp of data architecture and pipeline design (SQL experience is a plus).
The ability to explain what you're building and why you're building it to technical teammates and client stakeholders alike.
Candidates must be U.S. citizens or lawful permanent residents and be willing to undergo a thorough background check as part of the employment process.

Nice To Haves

Experience with AI agent development and orchestration frameworks.
Prior work in a consulting or professional services environment.
Experience with the Microsoft AI ecosystem and how tools like Copilot and Azure AI can be applied to improve workflows and productivity.

Responsibilities

Build and deploy AI agents, LLM-powered applications, and intelligent automation solutions, primarily in the Microsoft ecosystem.
Integrate large language models (LLMs) into client workflows via prompt engineering, fine-tuning, and API integration.
Design and implement data strategies, pipelines, and architectures that support AI use cases.
Develop and maintain APIs and system integrations that connect AI solutions to existing infrastructure.
Architect and deploy solutions on cloud platforms with a focus on reliability and scale.
Collaborate with the AI Solutions Consultant and clients to ensure technical solutions are aligned to business goals.
Apply responsible AI practices, including governance, bias evaluation, and explainability to every engagement.
Stay ahead of emerging AI tools, frameworks, and platforms and bring that knowledge into our practice.