Internal Forward Deployed Engineer, Entry Level

Associate Applied AI Engineer

Locations: United States - Waltham, MA, Cary, NC, or Westfield, IN

About Us:

We are dealer focused and OEM aligned. We are a leading ERP & DMS software and solutions provider to dealers and rental companies of heavy equipment. We specialize in working with the construction, mining, forestry, material handling, and agriculture industries. Today, we have over 800 employees, offices on four continents, and customers in over 20 countries. We are privately held, and our headquarters are in beautiful Cary, NC. We are actively seeking talented individuals to join our team and help us aggressively grow our international & North American footprint for both our 100% cloud-based ERP, DMS, and Rental solutions.

Why work for VitalEdge?

We don’t just sell technology, we enable transformation that results in broader societal benefits like building homes and critical infrastructure, growing food and delivering all sorts of products we all rely on for daily life. We exist to ultimately equip the world to keep running. We have more than 60 years of combined experience and three industry-leading software suites and associated apps, with which we will drive the market forward. It’s an exciting time to work for VitalEdge, join us!

Position Overview:

VitalEdge is building a Forward Deployed Engineering team focused on applying AI to high-priority business problems. The team works directly with business leaders to identify opportunities and turn them into production-ready AI solutions, including automation, agentic workflows, and AI-powered process improvements.

This is an early-career engineering role for someone with strong computer science fundamentals and hands-on experience with AI/ML. Working alongside a Senior Forward Deployed Engineer and other engineers, you’ll design, build, test, and deploy AI applications across initiatives such as data migration, ticket deflection/automation, and AI-assisted software development.

The role is highly hands-on and stays close to the code, but also requires understanding business processes and translating ambiguous problems into practical technical solutions. The ideal candidate is a curious, fast-learning builder who cares not just about building the technology, but whether it is actually adopted and delivers measurable business value.

Responsibilities:

Build and Deploy AI Solutions

• Develop components of AI agents, workflow automations, and AI-enabled applications under the guidance of the Senior FDE.
• Build integrations with APIs, databases, enterprise systems, and external tools.
• Support the development of the modern agentic engineering stack, including context engineering, harness engineering, loop engineering, graph engineering, retrieval-augmented generation (RAG), MCP-based tool integrations, and multi-agent orchestration.
• Write clean, tested, maintainable code and contribute to evaluations (evals), deployment, monitoring, feedback loops, and production support.

Translate Business Workflows into Technical Builds

• Participate in working sessions with functional teams to understand business processes, pain points, data, and requirements.
• Turn defined business needs into technical tasks, prototypes, and production components.
• Test solutions with users, incorporate feedback, and help improve adoption and measurable business impact.

Build Repeatable Capability

• Contribute reusable code, prompt patterns, evaluation assets, technical documentation, and implementation playbooks.
• Capture lessons from each deployment so future initiatives can move faster.
• Stay current on emerging AI capabilities, engineering patterns, and tools, and apply them pragmatically to business problems.
• Develop the technical judgment and delivery skills required to independently own larger solution components over time.

Qualifications:

Required

• Bachelor’s or Master’s degree completed recently in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, or a related technical discipline.
• Strong programming fundamentals and practical experience with Python through coursework, internships, research, open-source work, or personal projects.
• Understanding of algorithms, data structures, APIs, databases, testing, and software development practices.
• Foundational understanding of generative AI, large language models, and modern AI application patterns, including how context, harnesses, loops, graphs, and evals work together in production agentic systems.
• Demonstrated ability to learn quickly, solve unfamiliar problems, and work effectively in an iterative environment.
• Clear communication skills and interest in understanding both the technical and business dimensions of a problem.

Preferred

• Internship, research, academic, hackathon, or project experience building AI, machine learning, data, or software applications.
• Exposure to and building AI agents, context engineering, harness engineering, loop engineering, graph engineering, RAG, tool calling, MCP, multi-agent orchestration, prompt engineering, or evaluation frameworks.
• Experience with Git, SQL, REST APIs, cloud platforms, containers, or CI/CD workflows.
• Familiarity with frameworks such as LangGraph, LangChain, Semantic Kernel, AutoGen, CrewAI, or comparable technologies.
• A portfolio, GitHub repository, capstone, or other work product demonstrating hands-on technical ability.