Patlytics

Product Manager

• Own a core product area: set the strategy, prioritize ruthlessly, and ship outcomes (not output) across modules like drafting, infringement analysis, invalidity research, or portfolio management.
• Live with customers: spend real time with patent attorneys and in-house IP counsel through discovery calls, design partnerships, and on-sites. Translate what you hear into product.
• Bridge law and AI: translate nuanced patent workflows (Office Action responses, claim charting, SEP analysis, invalidity contentions) into elegant, scalable software.
• Prompt Engineering: Design, test, and iterate on complex LLM prompts and AI agents to ensure our models output highly accurate, citation-backed, and legally sound results.
• Define and move the metrics: instrument what matters, then drive measurable impact on activation, adoption, retention, and customer outcomes.
• Drive product velocity: maintain a rapid shipping cadence without sacrificing the enterprise-grade accuracy, auditability, and security our customers demand.

Product Designer

• Design end-to-end experiences across Patlytics' core workflows, including patent search, claim charting, portfolio analysis, prosecution, and litigation support, ensuring every interaction helps users leverage AI with confidence and clarity
• Be the voice of the customer in every design decision. Conduct user research directly with patent attorneys, IP counsel, and legal operations teams. Sit in on deployments. Watch real usage. Let what you learn reshape what you build
• Make AI legible. Design interfaces that surface AI-generated insights (prior art results, claim mappings, portfolio analytics) in ways that are transparent, verifiable, and actionable. Help users understand what the AI did, why, and how to act on it
• Stay at the forefront of AI interaction design, keeping up with the latest in LLM-powered interfaces, retrieval-augmented generation, agentic workflows, and emerging patterns for human-AI collaboration, then bring those ideas into the product
• Drive design through the full lifecycle, from early discovery and concept exploration through high-fidelity prototyping, usability testing, and post-launch iteration. Own the quality of the shipped experience, not just the mockup
• Create scalable design systems and patterns that bring consistency across a rapidly expanding product surface while remaining flexible enough for the specialized needs of different IP workflows

Senior Product Designer

• Own product outcomes for a portfolio of Patlytics' highest-impact enterprise accounts, including AmLaw firms and corporate IP teams, driving adoption from contract through full production
• Build trusted advisory relationships with senior patent attorneys, IP partners, and general counsel, becoming the person they turn to for what's possible with AI
• Stay at the forefront of AI, keeping up with the latest in LLMs, retrieval, reasoning, and agent architectures, and figure out how to apply these advances to patent search, claim analysis, portfolio management, prosecution, and litigation workflows
• Translate customer reality into product direction by curating, synthesizing, and prioritizing feedback with specificity and judgment. Not relaying feature requests, but articulating tradeoffs so product and engineering can make better decisions
• Drive deployments through the change management, enablement, and adoption challenges that determine whether AI actually transforms how a team works
• Create training materials, onboarding content, and use-case playbooks, both internal and external-facing, so that what works in one account can scale across many

Forward Deployed Product Manager

AI Engineer

• Develop and deploy robust, scalable AI/ML algorithms for cutting-edge IP applications
• Design, implement, and iterate on multi-step LLM pipelines for patent claim analysis, infringement detection, and prior art search, including the model selection, prompt architecture, and structured output contracts that define product quality
• Build and maintain a rigorous evals framework: define success metrics per pipeline stage, curate golden datasets from real IP cases, and run continuous regression testing to catch degradation before users do
• Develop retrieval systems (vector search, BM25 hybrids, re-ranking) optimized for patent corpus characteristics, long documents, technical claim language, biological sequence identifiers
• Architect and ship agentic workflows within our Agent layer, coordinating tool use, memory, and multi-turn reasoning over complex IP research tasks
• Develop data classification techniques and post-training on the latest LLMs
• Collaborate with patent attorneys and domain experts to encode expert judgment into prompts, rubrics, and fine-tuning datasets, then measure whether it worked Own cost, latency, and quality tradeoffs for production inference: prompt caching strategies, context window management, batching, and model migration planning on AWS, GCP and other LLM providers.
• Partner with a highly talented cross functional group of researchers, applied scientists, engineers, and product managers to build and evolve the (your company’s platform, product, solution, etc.)
• Work with large, complex data sets, solve difficult, non-routine analysis problems, and apply advanced analytical methods as needed
• Partner with the Leadership Team to align development strategies with key product requirements and long-term technical roadmap
• Build tools to monitor data pipeline performance, data quality and models in production
• Perform unit testing, profiling, and parameter tuning
• Collaborate with data engineers & platform team to implement data pipelines and robust production real-time and batch decisioning solutions
• Lead ongoing R&D of new technologies, data sources and data science & optimization tools
• Improve existing machine learning methodologies by developing new sources and testing enhancements, running computational experiments, and fine-tuning parameters