Top Tech Jobs & Startup Jobs in NYC, NY

Leads product portfolio management across capital planning, investment prioritization, profitability analysis, product rationalization, taxonomy, business-case tracking, resource planning, and leadership reporting. Partners with Product, Engineering, Finance, Operations, and Strategy to align portfolio decisions with corporate strategy and financial outcomes. Uses AI and analytics to improve decision-making, synthesize complex information, and guide product investments.

Leads technical discovery, solution architecture, demonstrations, proposals, and technical deal support for enterprise media and SaaS customers. Designs scalable AWS and Azure solutions, advises on deployment and integrations, manages technical risks, and supports post-sale implementation and optimization. Partners with commercial, product, engineering, and delivery teams while influencing product direction and developing presales tools and technical playbooks.

Creates and maintains practical legal content on public and private securities offerings, monitors capital markets developments, and supports AI-powered legal product development. The role requires advising issuers and underwriters, collaborating with product teams and external contributors, responding to customer inquiries, and supporting sales and marketing. Candidates need a JD, at least eight years of relevant legal experience, strong writing and technology skills, and expertise in US securities law.

As a Lead Applied Scientist, you will define research strategy, mentor teams, and innovate AI/ML solutions for legal and other professional sectors.

Leads a team of four sales executives selling Thomson Reuters’ market and financial insights platforms and advisory services to large law firms. Owns team quota, sales strategy, pipeline forecasting, complex deal support, executive relationships, cross-functional collaboration, recruiting, and seller development. The role requires consultative enterprise selling, strong business acumen, Salesforce proficiency, and periodic travel.

The Senior Product Manager will lead AI-enabled legal research and litigation workflow products for Westlaw. Responsibilities include shaping product strategy, evaluating ideas, collaborating with engineering and data science teams, improving user experiences, integrating complex systems, and designing evaluation frameworks to ensure accurate, compliant, and contextually relevant outputs. The role also requires engaging legal professionals and stakeholders to validate concepts and maintain focus on customer needs.

Leads the design, development, evaluation, and production deployment of document understanding systems for legal, tax, and accounting content. Responsibilities include semantic chunking, document enrichment, hierarchical classification, entity and citation extraction, knowledge graph construction, LLM post-training, model distillation, synthetic data generation, and evaluation framework development. The role guides architecture and AI strategy, partners with engineering on scalable delivery, influences leadership, and mentors applied scientists and ML practitioners.

Build, train, evaluate, and deploy production machine learning and LLM systems for legal document intelligence. Develop NLP solutions for information extraction, summarization, search, AI agents, and document analysis. Create scalable ML pipelines, evaluation frameworks, and reliability metrics while optimizing model performance. Collaborate with engineering, product, legal, data, and security teams to deliver secure AI capabilities and translate business problems into production solutions.

Design and lead enterprise AI systems using generative AI, RAG, knowledge graphs, and autonomous agents. Define technical strategy, evaluate emerging AI technologies, and guide architecture and roadmaps. Mentor engineers, champion MLOps and LLMOps governance, and ensure security, testing, monitoring, and observability. Collaborate with research, engineering, design, and product teams to deliver scalable customer-facing solutions while optimizing latency, cost, and user experience.

Designs and leads enterprise AI systems for legal research, including RAG pipelines, knowledge graphs, autonomous agents, and AI platforms. Provides technical strategy, architecture, mentoring, governance, testing, observability, and operational leadership. Partners with research, engineering, design, and product teams to launch scalable, secure AI products. Requires hands-on software engineering expertise in generative AI, cloud-native systems, APIs, distributed systems, and production AI deployments.