Associate AI Engineer

Job Description

Job Description

Associate AI Engineer The Role We're hiring an Associate AI Engineer to work across LLMs, agentic workflows, and advanced AI tooling, building solutions that streamline operations and eliminate repetitive work across the business. You'll scope, build, ship, and maintain real systems, with security and governance built in from the start. You'll work with stakeholders across the business, navigate practical constraints and deadlines, and get mentorship from a team that already has AI systems running in production. If you want to move fast, build real tools, and make an immediate impact, this is your chance. What You Will Do Own AI projects end to end: problem scoping, design, prompt engineering, integration, testing, deployment, and documentation. Build and deploy agentic workflows and LLM powered tools that solve real operational problems. Go beyond basic prompting to design reliable AI systems, structuring LLMs into multi-step agent workflows with clear handoffs and built in checks at each step. Design multi-agent systems where separate agents coordinate with each other and hand off work along the way. Work directly with stakeholders across the business to turn vague problems into clear requirements with defined inputs, outputs, and success criteria. Run proofs of concept to pressure test ideas, then take the ones that work into production. Monitor, debug, and improve systems already running, including troubleshooting when something breaks. Build the evals and metrics that measure whether an AI system is working and delivering business value. Apply security and governance practices, including risk tiering, guardrails, and registry entries, to everything you build. Evaluate advanced AI tools and platforms against real business requirements. What We Are Looking For This role is designed for early career talent, recent graduates and career changers who bring relevant coursework, hands on project work, or internship experience rather than years on the job. Bachelor's or master's degree in Computer Science, Information Systems, AI/ML, or a related technical field, or equivalent practical experience. Demonstrated experience building with LLMs or agentic workflows, such as a capstone project, hackathon project, internship deliverable, or personal project. Enthusiasm for AI technologies demonstrated through academic projects, hackathons, etc. Proficiency in Python and the ability to read and debug code written by others. You want to understand how LLMs and agentic systems actually work, not just how to use them. An instinct for security and responsible AI practice; you think about what could go wrong before it does. Strong written communication. You can explain your reasoning, tradeoffs, and what you'd change next time in a way others can act on. Ability to take ownership of a project and drive it to completion. Preferred Qualifications Experience with agentic frameworks such as LangChain, LangGraph, or CrewAI Exposure to evaluation frameworks or techniques for testing AI system performance Familiarity with tracing or observability tools used to debug multi-step agent behavior Experience with API integration work or connecting agents to external tools and data Prior exposure to AI security, red teaming, or governance practices Familiarity with cloud platforms such as AWS, GCP, or Azure Why You Will Love It Here You'll work alongside people actively building and running AI systems in production, not just talking about it. You'll get exposure to frontier models, agentic frameworks, and emerging techniques like multi-agent orchestration as part of your day to day work, not as a side interest. You'll be part of building Jumpmind's AI practice at a point where your decisions still shape how it works. You'll learn to build AI responsibly and securely from day one, not as an afterthought once something is already in production. Final Word If you're ready to build real AI systems and learn how enterprise technology decisions get made, let's talk.