AI Engineer, Graduate Level

NewRocket

Early-career AI Engineer building Claude-powered generative and agentic AI solutions. Supporting RAG, automation, evaluation, and ServiceNow integrations for enterprise clients.

Posted 8/26/2026full-timeRemote • 🇺🇸 United StatesEntry LevelWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in developing and integrating AI-enabled applications and workflows, with a strong foundation in programming languages such as Python and JavaScript. Proficient in generative AI, prompt engineering, and responsible AI principles, while effectively collaborating with cross-functional teams.

Highest-signal resume keywords

Generative AI DevelopmentPrompt EngineeringPython ProgrammingServiceNow IntegrationMachine Learning Concepts

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Programming LanguagesAPIsDatabasesSoftware Engineering ConceptsMachine LearningData ScienceWorkflow AutomationModel EvaluationCloud-Based ApplicationsResponsible AI Principles

Soft Skills

Problem-SolvingAttention to DetailCuriosityCommunication Skills

Tools & Technologies

GitREST APIsSQLDockerLLM APIsLangChainLangGraphLlamaIndexAWSMicrosoft Azure

Certifications & Qualifications

MCP

Industry Keywords

AI-Enabled ApplicationsWorkflow OrchestrationHuman-in-the-Loop ReviewData PrivacyAgile Software Development

Tech Stack

Tools & technologies

AWSAzureCloudDockerJavaJavaScriptPythonServiceNowSQLTypeScript

About the role

Key responsibilities & impact

Build, test, maintain, and document AI-enabled applications, workflows, and reusable accelerators
Develop generative AI and LLM prototypes and proof-of-concepts using Claude, RAG, APIs, and workflow automation tools
Support agentic AI solutions using enterprise context, approved tools/APIs, and workflow orchestration
Assist with prompt and context engineering, structured outputs, function calling, human-in-the-loop review, and workflow orchestration
Integrate AI capabilities with enterprise platforms, including ServiceNow
Prepare data and documents, including ingestion, chunking, embedding, retrieval, prompt development, evaluation, and testing
Assess model and workflow performance for accuracy, relevance, groundedness, reliability, latency, cost, safety, and user experience
Develop test cases, evaluation datasets, monitoring approaches, feedback loops, validation, fallback handling, and escalation workflows
Apply responsible AI principles and safeguards for sensitive data, access controls, prompt injection, and unsafe tool execution
Collaborate with product, engineering, design, data science, ServiceNow platform, and consulting teams
Participate in requirements gathering, solution design, sprint planning, code reviews, and retrospectives
Support client-facing technical research, demos, proof-of-concepts, and implementation activities
Contribute to documentation, technical playbooks, reusable components, prompt libraries, evaluation assets, and knowledge-sharing sessions
Stay current on AI technologies, Anthropic and Claude capabilities, and enterprise use cases
Research and propose generative and agentic AI applications for enterprise workflows

Requirements

What you’ll need

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 context windows, token usage, embeddings, vector search, RAG, tool use/function calling, structured outputs, and model evaluation
Familiarity with Git, REST APIs, SQL, Docker, LLM APIs, LangChain, LangGraph, LlamaIndex, or cloud AI services
Foundational understanding of responsible AI concepts, data privacy, model limitations, human oversight, and safe AI deployment
Ability to communicate technical concepts clearly to technical and non-technical stakeholders
Strong problem-solving skills, curiosity, attention to detail, and willingness to learn
Preferred: experience with Claude, Anthropic API, Anthropic Console, Anthropic Academy, ServiceNow, AWS, Microsoft Azure, Google Cloud, MCP, or agile software development

Benefits

Comp & perks

Diverse and inclusive workplace
Equal opportunity workplace and affirmative action employer
Disability accommodation available upon request
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
Hands-on experience building enterprise-grade generative and agentic AI solutions
Exposure to Anthropic-aligned practices and technical education opportunities
Experience across the end-to-end lifecycle of AI product and solution development