Senior Applied Machine Learning Engineer – Agentic Workflows

Location: Remote (Continental US) Department: Product & Engineering Clearance: U.S. Citizen, Public Trust eligible Role Overview We are seeking a senior-level applied machine learning engineer to design and deliver advanced AI capabilities powered by large language models for litigation, investigations, and data breach workflows involving large-scale document collections. This role focuses on applying LLMs, retrieval-augmented generation (RAG), and agentic decision-support techniques to help legal and breach teams reason over complex datasets, improve consistency and quality in review outcomes, and support defensible decisions related to responsiveness, privilege, confidentiality, and sensitive data exposure. The work emphasizes grounded outputs, explainability, and operational reliability over experimental approaches. You will build AI capabilities that operate on real-world data at scale, where answer quality, traceability, and trust are critical. Key Responsibilities Design and implement applied ML and GenAI solutions that support document review and analysis across litigation, investigations, and data breach workflows Build LLM-powered systems that enable corpus-level reasoning, allowing users to ask questions of large document sets and receive grounded, evidence-backed outputs Design and deploy retrieval-augmented generation (RAG) approaches that combine semantic retrieval, document context, and generative reasoning to produce explainable results Develop agentic or multi-step reasoning workflows that decompose complex review or analysis tasks into bounded, auditable decision steps Build systems that generate summaries, classifications, and decision rationales relevant to review quality, responsiveness, privilege, confidentiality, and exposure assessment Apply grounding and citation techniques to ensure model outputs remain anchored in authoritative document content and supporting evidence Design decision-support logic that incorporates confidence thresholds, review gating, and human judgment where appropriate Integrate AI services into production-grade systems with attention to performance, scalability, auditability, and failure handling Collaborate with product, platform, and domain experts to ensure solutions align with real-world litigation and breach response practices Monitor system behavior in production and continuously improve outcomes based on user feedback and observed decision quality Required Skills & Experience Hands-on experience working in or leading teams utilizing large language models (LLMs), retrieval-augmented generation (RAG), embeddings, and agentic AI techniques in user-facing applications Strong background in applied machine learning with experience deploying ML systems in production environments Experience designing or operating semantic retrieval, ranking, or AI-augmented search systems over large document collections Experience building systems that operate over large, heterogeneous, and imperfect document datasets Ability to design grounded, explainable AI outputs that support defensible legal and breach-related decision-making Experience translating ambiguous legal, investigative, or compliance requirements into measurable technical behavior Strong software engineering fundamentals, including testing, versioned deployments, and maintainability Comfort operating in domains where accuracy, consistency, automation, and risk must be carefully balanced Preferred Qualifications Experience with eDiscovery, litigation support, internal investigations, or data breach response Familiarity with legal review concepts such as responsiveness, privilege, confidentiality, issue tagging, and exposure assessment Experience working in regulated or compliance-driven environments Experience with hybrid AI systems combining learned models with structured signals, rules, or human feedback Job Type: Full-time Pay: $130,000.00 - $170,000.00 per year Benefits: 401(k) 401(k) matching Dental insurance Health insurance Paid time off Professional development assistance Vision insurance Work Location: Remote