AI Engineer-Anthropic-University/Graduate Level - UK

NewRocket is an AI-first Elite ServiceNow Partner and Anthropic partner that helps enterprises adopt and operationalize trusted AI solutions. The AI Engineer – Campus and Graduate Level will support the design, development, testing, and deployment of AI-enabled enterprise solutions, including Claude-powered applications, agentic workflows, RAG, intelligent automations, and ServiceNow integrations. The role also involves evaluation, responsible AI, security, cross-functional collaboration, and continuous improvement across the AI solution lifecycle.

What you'll do:

• 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
• 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

What they're looking for:

• Currently pursuing or recently completed a degree in **Computer Science, Engineering, Data Science, Artificial Intelligence, Machine Learning**, or a related technical discipline
• **1–3 years of relevant experience** through internships, co-ops, research, freelance work, academic projects, or professional roles
• Experience with one or more programming languages, preferably **Python**, **JavaScript/TypeScript**, Java, or similar languages
• Foundational understanding of software engineering concepts, APIs, databases, source control, and cloud-based applications
• Exposure to generative AI, LLMs, prompt engineering, machine learning, data science, or automation concepts
• Familiarity with LLM application concepts such as context windows, token usage, embeddings, vector search, RAG, tool use/function calling, structured outputs, and model evaluation
• Familiarity with tools or frameworks such as Git, REST APIs, SQL, Docker, LLM APIs, LangChain, LangGraph, LlamaIndex, or cloud AI services
• Foundational understanding of responsible AI concepts, including data privacy, model limitations, human oversight, and safe AI deployment
• Strong problem-solving skills, curiosity, attention to detail, and willingness to learn in a fast-paced environment
• Ability to communicate technical concepts clearly to both technical and non-technical stakeholders
• Experience building AI, automation, chatbot, workflow-based, or data-driven projects through coursework, research, internships, hackathons, or personal projects
• Exposure to **Claude**, the Anthropic API, Anthropic Console, Anthropic Academy learning, or Claude-focused implementation guidance

Benefits:

• Hands-on experience building enterprise-grade generative and agentic AI solutions, including Claude-powered applications where appropriate.
• Exposure to Anthropic-aligned practices for prompt and context engineering, RAG, tool use, structured outputs, model evaluation, and responsible AI.
• Experience across the end-to-end lifecycle of AI product and solution development—from discovery and prototyping to deployment, monitoring and continuous improvement.
• Mentorship from experienced AI, engineering, product, ServiceNow, and consulting professionals.
• Opportunities to contribute to client-facing proofs-of-concept, reusable AI accelerators, Agent Packs, and production implementations.
• A strong foundation for a career in AI engineering, software development, data science, enterprise technology consulting, or AI product development.