AI Engineer-Anthropic-University/Graduate Level - Netherlands/Western Europe

Job Description

AI Engineer – Campus and Graduate Level Experience: 1–3 years of relevant experience through internships, academic projects, research, freelance work, or professional roles Location: [Location / Hybrid / Remote] Travel to clients and conferences as needed. Reports to: Agentic AI Architect / Senior Forward Deployed AI Engineer Why NewRocket NewRocket is the AI-first Elite ServiceNow Partner that activates real value on the Now Platform. As a trusted advisor to enterprise leaders, we combine industry expertise, human-centered design, and enterprise-grade AI to help organizations navigate change and scale with confidence. With two decades of experience guiding clients to realize the full potential of the ServiceNow AI Platform, we are one of the largest pure-play ServiceNow partners—uniquely focused on enabling enterprises to adopt AI they trust and that delivers lasting business value. NewRocket is also a proud Anthropic partner/vendor, expanding our ability to help enterprises responsibly adopt and operationalize Claude-powered AI solutions. Through this relationship, NewRocket is building advanced capabilities in generative AI, agentic workflows, secure enterprise knowledge experiences, and AI-enabled automation. Our teams apply Anthropic-aligned practices in prompt and context engineering, retrieval-augmented generation (RAG), tool use, structured outputs, model evaluation, safety, governance, and human-in-the-loop controls. As an early-career AI Engineer at NewRocket , you will have the opportunity to learn and apply these emerging enterprise AI practices while helping build practical solutions that connect Claude and other AI technologies with ServiceNow, enterprise data, and business workflows. We #GoBeyondWorkflows to create new kinds of experiences for our customers. Come join our Crew! Role Overview NewRocket is seeking a hands-on AI Engineer – Campus and Graduate Level to support the design, development, testing, and deployment of AI-enabled solutions for enterprise clients. This role is ideal for an early-career engineer with foundational experience in software development, data, and generative AI who is eager to work on practical, high-impact applications of AI—including Claude-powered applications, agentic workflows, intelligent automations, retrieval-augmented generation (RAG), and ServiceNow-based solutions. You will work closely with AI engineers, product managers, data scientists, platform teams, and client-facing consultants to prototype and deliver scalable AI capabilities. You will gain exposure to the full AI solution lifecycle, from use-case discovery and proof-of-concept development through production rollout, evaluation, monitoring, and continuous improvement. Travel to clients and conferences as needed. Key Responsibilities AI Solution Development Assist in building, testing, maintaining, and documenting AI-enabled applications, workflows, and reusable accelerators. Develop prototypes and proof-of-concepts using generative AI, large language models (LLMs), including Claude and other model providers as appropriate, RAG, APIs, and workflow automation tools. Support the development of agentic AI solutions that can use enterprise context, call approved tools or APIs, and help orchestrate enterprise processes. Assist with prompt and context engineering, including instruction design, examples, structured inputs, response formatting, and output constraints. Help build AI applications using structured outputs, tool use/function calling, human-in-the-loop review, and workflow orchestration patterns. Help integrate AI capabilities with enterprise platforms, including ServiceNow, where applicable. Write clean, maintainable, secure, and well-documented code following engineering best practices. Retrieval, Data, Evaluation & Quality Support data preparation, document ingestion, chunking, embedding, retrieval, prompt development, evaluation, and testing activities for AI solutions. Assist with RAG solutions that ground AI responses in authorized enterprise knowledge sources and data. Help assess model and workflow performance across accuracy, relevance, groundedness, reliability, latency, cost, safety, and user experience. Assist with the development of test cases, evaluation datasets, monitoring approaches, and feedback loops for AI applications. Support techniques that improve reliability and user trust, such as output validation, citation or source-grounding patterns, fallback handling, confidence thresholds, and escalation workflows. Identify issues, document findings, and contribute to iterative improvements across AI prototypes and production solutions. Responsible AI & Security Apply responsible AI principles in the development and testing of AI solutions, including awareness of model limitations, hallucinations, bias, privacy, and appropriate human oversight. Help implement safeguards for sensitive data, access controls, authorized data use, prompt-injection risks, and uns