Genesis10 is currently seeking a Senior Generative AI Engineer - Remote for a direct hire opportunity with a Global Law Firm located in New York, NY. You will join as a Senior Generative AI Engineer on the AI Acceleration Team, reporting to the Data Science Manager, and working with engineers, data scientists, and legal domain experts. This role is for an engineer who can own the full lifecycle of LLM-powered products, from rapid prototyping through production deployment. You will design, ship, and operate AI systems that extract intelligence from complex legal documents, orchestrate multi-step agent workflows, and deliver measurable accuracy improvements under real-world latency and cost constraints. Responsibilities: * Own production AI systems end-to-end: Design, build, deploy, and monitor LLM-powered document analysis pipelines (extraction, classification, risk flagging) that serve lawyers daily, meeting defined latency SLAs and accuracy benchmarks * Transform legal data into structured, high-quality datasets that power our AI systems * Design and ship agent workflows: Architect multi-step, multi-agent systems for complex legal tasks (e.g., due diligence, contract review, regulatory analysis) with robust state management, tool calling, and human-in-the-loop checkpoints * Define evaluation and governance frameworks: Build golden test sets, automated eval pipelines, and regression suites. Implement guardrails (prompt firewalls, output filters, PII redaction) to ensure safety and regulatory readiness * Optimise cost and performance: Manage token budgets across model providers, implement caching and batching strategies, and make data-driven build-vs-buy decisions on model selection (API-served, open-source vs. proprietary) * Collaborate with lawyers and product to translate ambiguous legal requirements Requirements: * At least 3 years of professional experience building and deploying AI systems, with at least 1-2 years focused on LLM/GenAI applications in production * Deep experience with document-heavy NLP: extraction from complex layouts (PDFs, tables, scanned documents), entity recognition, and structured output generation * Proven ability to design and optimise RAG pipelines and prompt architectures for accuracy, cost, and latency in production * Strong Python engineering skills, with clean, tested, production-ready code * Familiarity with at least one LLM orchestration framework (LangGraph, LlamaIndex, or equivalent) and at least one vector database (Pinecone, Weaviate, pgvector, or equivalent) * Experience with cloud platforms (AWS or Azure preferred) for deploying and monitoring LLM-backed services, including CI/CD, containerisation, and observability tooling * Experience designing systematic evaluation methodologies for generative AI (automated evals, golden test sets, faithfulness/hallucination metrics) * Ability to own a workstream end-to-end: scope it, build it, evaluate it, ship it, and clearly communicate tradeoffs and results to non-technical stakeholders * Comfortable with CI/CD pipelines, code review, version control, and shipping behind feature flags * A genuine interest in legal work is essential Desired skills: * Experience in a startup or high-velocity AI team where you shipped frequently and wore multiple hats * Master's or PhD in Computer Science, Computational Linguistics, Mathematics, or a related quantitative field * Vector databases, retrieval systems, or knowledge graphs experience * Familiarity with model-serving infrastructure (vLLM, TGI, Triton) and GPU-aware deployment * Domain experience in legal tech, compliance tech, or other regulated industries where accuracy and auditability are non-negotiable * Published research or significant open-source contributions in NLP, information retrieval, or generative AI * Experience with knowledge graphs, ontologies, or semantic reasoning over structured legal data *