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# Junior Generative AI Engineer - Remote

- **Company:** Genesis10
- **Location:** New York, NY, United States (Remote available)
- **Experience:** Starter
- **Salary:** $120,000 - $160,000
- **Contract:** Internship / Graduate position
- **Skills:** HTML, Application Programming Interfaces (APIs), Amazon Web Services, Microsoft Azure, Cloud Computing, Computational Linguistics, Databases, Content Analysis, Text Processing, Information Retrieval, Python (Programming Language), Open Source Technology, Parsing, OpenAI, Software Engineering, Pinecone, Retrieval-Augmented Generation, Large Language Models, Apache Spark, Hallucination Detection, Llamaindex, Generative AI, Pgvector, Information Technology, Weaviate, FAISS, Data Pipelines, Automation Anywhere, Databricks
- **Published:** October 29, 2026
- **Apply:** https://www.thejobnetwork.com/job/11a20f8b-7eed-489a-80da-ec9367a72772/junior-generative-ai-engineer-remote

## About the Role

* Some software development experience (internships, co-ops, or substantial academic/personal projects count)
 * Hands-on exposure to LLM/GenAI tools or APIs and some experience working with text data (parsing PDFs or HTML, basic text processing, or using an LLM for extraction or classification)
 * Solid Python skills and comfort with basic SQL
 * Conceptual understanding of how RAG pipelines work, with ideally some hands-on experience
 * Familiarity with at least one LLM API (OpenAI, Anthropic, or similar)
 * Basic familiarity with cloud platforms (AWS or Azure) and an understanding of how to evaluate generative AI outputs (accuracy, faithfulness, hallucination)
 * Strong communication skills: ability to explain what you've built, ask good questions, and clearly describe problems and trade-offs to both technical and non-technical teammates

Desired skills:

 * Experience in a hackathon, open-source project, or fast-paced team environment where you shipped working software quickly
 * A degree (Bachelor's or Master's) in Computer Science, Mathematics, Computational Linguistics, or a related quantitative field
 * Exposure to an orchestration framework (LangChain, LlamaIndex) or a vector database (Pinecone, Weaviate, pgvector, FAISS)
 * Curiosity about model-serving infrastructure (vLLM, TGI) or how open-source models are deployed
 * Any exposure to legal tech, compliance tech, or other regulated industries where accuracy and auditability are critical
 * A personal blog, portfolio project, or open-source contribution demonstrating your interest in NLP, information retrieval, or generative AI
 * Any experience with Spark, Databricks, or data pipeline tooling

## Description

* Under the guidance of senior engineers, help build, test, and improve LLM-powered document analysis features (extraction, classification, risk flagging)
 * Help clean, structure, and label legal data to power AI systems, building the data pipelines that make models work well in practice
 * Implement bounded components of multi-step AI workflows for legal tasks (e.g., due diligence, contract review) by writing tool integrations, prompt chains, and retrieval logic
 * Write test cases, contribute to automated evaluation pipelines, and help maintain regression suites
 * Participate in cross-functional sessions to understand legal workflows, contribute to acceptance criteria, and iterate based on user feedback and evaluation results