AI Engineer/Anthropic-Campus Hire - US West

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.

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.
• Assist with integrating 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.
• Assist with assessing model and workflow performance across accuracy, relevance, groundedness, reliability, latency, cost, safety, and user experience.
• Assist with developing test cases, evaluation datasets, monitoring approaches, and feedback loops for AI applications.
• 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.
• Implement safeguards for sensitive data, access controls, authorized data use, prompt-injection risks, and unsafe or unintended tool execution.
• Support human-in-the-loop workflows for sensitive, high-impact, low-confidence, or exception-based AI decisions.
• Document solution behavior, known limitations, test results, and operational considerations for internal teams and client stakeholders.
• Cross-Functional Collaboration
• Collaborate with product, engineering, design, data science, ServiceNow platform, and consulting teams to translate business needs into technical solutions.
• Participate in requirements gathering, solution-design sessions, sprint planning, code reviews, and retrospectives.
• Support client-facing teams with technical research, demos, proof-of-concept development, and implementation activities.
• Communicate technical concepts, solution behavior, and findings clearly to both technical and non-technical stakeholders.
• Contribute to internal documentation, technical playbooks, reusable components, prompt libraries, evaluation assets, and knowledge-sharing sessions.
• Ai Innovation & Research
• Stay current on emerging AI technologies, frameworks, Anthropic and Claude capabilities, and enterprise use cases.
• Complete relevant Anthropic training, partner enablement, and technical education opportunities as available through NewRocket’s partnership.
• Research opportunities to apply generative and agentic AI to improve operational efficiency, employee experiences, customer service, knowledge management, and enterprise workflows.
• Contribute ideas for new AI capabilities, reusable intellectual property, Agent Packs, accelerators, and product enhancements.

Required Qualifications

• 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.

Preferred Qualifications

• 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.
• Experience using LLM APIs to build conversational AI, document-processing, summarization, search, knowledge-assistant, or workflow-automation applications.
• Understanding of RAG, vector databases, embeddings, semantic retrieval, AI agents, tool use, or human-in-the-loop workflow design.
• Familiarity with ServiceNow, including platform development, workflow automation, Virtual Agent, Predictive Intelligence, Now Assist, AI Agents, IntegrationHub, or Flow Designer.
• Exposure to cloud platforms such as AWS, Microsoft Azure, or Google Cloud.
• Familiarity with Model Context Protocol (MCP) concepts, secure API integration patterns, or connecting AI applications to enterprise tools and data sources.
• Experience working in an agile software-development environment.
• Interest in enterprise consulting, digital transformation, and applying AI to real-world business challenges.