Junior Generative AI Engineer

3 days ago

Base Salary

$120k - $160k/yr

Responsibilities

Help build, test, and improve LLM-powered legal document analysis features for extraction, classification, and risk flagging.
Clean, structure, and label legal data and help build data pipelines that support AI systems.
Implement bounded components of multi-step AI workflows, including tool integrations, prompt chains, and retrieval logic.
Write test cases, contribute to automated evaluation pipelines, and maintain regression suites.
Gain exposure to model selection, token budgets, caching strategies, output filters, PII redaction, and production AI reliability practices.
Collaborate with lawyers, engineers, data scientists, and product partners to understand workflows, define acceptance criteria, and incorporate feedback.

Some software development experience through internships, co-ops, or substantial academic or personal projects, including hands-on exposure to LLM or generative AI tools or APIs.
Solid Python skills, comfort with basic SQL, and some experience working with text data such as PDFs or HTML.
Conceptual understanding of RAG pipelines and familiarity with at least one LLM API, such as OpenAI or Anthropic.
Basic familiarity with AWS or Azure and an understanding of generative AI evaluation concepts including accuracy, faithfulness, and hallucination.
Ability to communicate clearly with technical and non-technical teammates and explain technical work, questions, problems, and trade-offs.
Experience with LangChain, LlamaIndex, or a vector database is a plus.
Preferred experience includes Pinecone, Weaviate, pgvector, FAISS, vLLM, TGI, Spark, Databricks, data pipeline tooling, retrieval systems, NLP, information retrieval, knowledge graphs, ontologies, semantic reasoning, legal technology, or regulated industries.
A bachelor's or master's degree in Computer Science, Mathematics, Computational Linguistics, or a related quantitative field is nice to have.

Remote-first work environment.
Dedicated senior engineer mentor for at least the first six months.
Structured 90-day onboarding covering the technology stack, legal domain fundamentals, and AI evaluation practices.
Regular pair-programming sessions and thorough, constructive code reviews.
AI safety and bias training covering non-deterministic failures, prompt injection, LLM bias, and responsible AI practices.
Clear progression framework from Junior to Mid-Level to Senior with regular check-ins and increasing ownership opportunities.
Comprehensive benefits package including health care benefits.

1,001-5,000 employees