NewRocket
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 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 to create new kinds of experiences for our customers. 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 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. What You Will Gain 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 . click apply for full job details
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 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 to create new kinds of experiences for our customers. 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 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. What You Will Gain 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 . click apply for full job details