Darrow

Description Who We Are You are looking for a role that challenges you intellectually and lets you build things that matter. You have an entrepreneurial mindset, you enjoy solving complex technical problems, and you thrive in a fast-paced startup environment. Most of all, you want your work to have meaning. We're Darrow – a fast-growing startup in the Legal Exposure Management space. We have an open, action-driven culture unlike any other. Our work starts from a simple idea: legal exposure should be visible while it's still possible to act on it. We've built a technology engine that scans massive amounts of public data to identify legal exposure and evaluate its financial value at sale, and every tool or workflow you build here moves that mission forward. We have one advantage technology and AI can't replicate: our people. More than 100 people worldwide, in Israel, US & Europe who are smart, humble, curious people who thrive at the intersection of law and AI, and we're looking for the leader who will protect and grow that edge as we scale. About the Role A Senior AI/ML Engineer role on our Data team, sitting at the intersection of AI engineering, data science, and data platform. You'll build agentic, LLM-based systems that turn vast amounts of unstructured information into high-quality structured signals — powering Darrow's products and surfacing legal risk — owning each solution across the full lifecycle, from exploration to production. You'll work closely with data engineers, data scientists, product managers, and legal experts to turn ambiguous problems into scalable AI capabilities. This is a hands-on role for someone with strong engineering judgment, deep data/ML expertise, and a focus on reliability beyond the prototype stage. What You'll Do • Design, build, deploy, and operate production AI systems: agentic, LLM-based extraction workflows and batch/online inference pipelines and owning them from exploration through deployment, monitoring, and iteration. • Define quality metrics and build evaluation datasets, testing processes, and feedback loops for ML and LLM systems; monitor accuracy, latency, cost, and data quality, and investigate and fix failures. • Explore large, complex datasets to surface useful features and patterns, and translate findings into production-grade implementations. • Partner with data engineers on ingestion, transformation, orchestration, and storage to deliver dependable data products. • Use AI-assisted coding tools (e.g., Claude) effectively while maintaining strong technical judgment and ownership of your systems. • Help shape engineering standards for production AI: testing, observability, reproducibility, data lineage, versioning, and safe deployment. Requirements What You Bring • 6+ years in ML engineering, AI engineering, data science, or backend engineering for data-intensive systems, with hands-on experience taking systems to production (deployment, monitoring, evaluation, versioning, improvement). • Strong Python skills and data orientation — SQL, NoSQL, data pipelines, and both structured and unstructured data. • Solid data science foundation: feature engineering, statistical reasoning, experiment design, error analysis, and relevant metrics (precision, recall, accuracy, coverage). • Experience with LLM-based applications: structured extraction, tool calling, agentic workflows, prompt design, embeddings, retrieval, and model evaluation. • Understanding of production AI tradeoffs, quality, latency, scalability, reliability, cost and experience integrating AI into batch, orchestration, API, or event-driven workflows. • Ability to work independently in ambiguous environments, breaking problems down and driving them to production. • Strong communication skills across engineering, data science, product, and domain-expert teams. Nice to Have • Document intelligence, information extraction, entity resolution, classification, ranking, or large-scale enrichment pipelines. • Experience building or operating agentic systems in production. • Natural Language Processing experience. • Familiarity with orchestration/ML tooling (Airflow, Dagster, Prefect, MLflow, or similar). • Experience with data warehouses, data lakes, vector databases, or modern data-processing frameworks. • Cloud-native experience: AWS, Docker, Kubernetes, IaC, CI/CD. • Experience with human-in-the-loop review or feedback-driven AI systems. • Familiarity with legal, financial, compliance, or other data-intensive domains where quality and explainability matter. What Success Looks Like • AI capabilities move reliably from experimentation to production, on systems engineers, scientists, and domain experts can depend on. • Agentic workflows deliver accurate, measurable structured data that strengthens Darrow's products and decision-making.

Description You are looking for a role that challenges you intellectually and lets you build things that matter. You have an entrepreneurial mindset, you enjoy solving complex technical problems, and you thrive in a fast-paced startup environment. Most of all, you want your work to have meaning. We're Darrow – a fast-growing startup in the Legal Exposure Management space. We have an open, action-driven culture unlike any other. Our work starts from a simple idea: legal exposure should be visible while it's still possible to act on it. We've built a technology engine that scans massive amounts of public data to identify legal exposure and evaluate its financial value at sale, and every tool or workflow you build here moves that mission forward. We have one advantage technology and AI can't replicate: our people. More than 100 people worldwide, in Israel, US & Europe who are smart, humble, curious people who thrive at the intersection of law and AI, and we're looking for the leader who will protect and grow that edge as we scale. We are looking for a talented Senior Product Marketing Manager to lead go-to-market for a new enterprise product, working hand in hand with our product and GTM teams in Tel Aviv. This role is critical in shaping a 0-to-1 product from the ground up: defining positioning and messaging, building sales enablement, and turning product vision into a repeatable enterprise sales motion. You'll bring a strong understanding of how complex enterprise deals are won, with experience crafting messaging that resonates with both technical and line-of-business buyers. If you're a strategic, hands-on product marketer who thrives in ambiguity and loves building what doesn't exist yet, we'd love to hear from you! Responsibilities: • Own positioning and messaging for an enterprise AI-powered software product from 0 to 1, from the first narrative through market validation and refinement • Translate competitive intelligence and customer insights into compelling pitch decks, messaging frameworks, and battlecards • Content creation: sales decks, demo narratives, objection handling, case studies, and training for teams selling to both line-of-business and technical buyers • Partner closely with the Product team in Tel Aviv as the voice of the customer, informing roadmap, packaging, and pricing decisions • Plan and lead product and feature launches end to end, aligning Product, Sales, and Marketing on timing, messaging, and success metrics • Drive adoption and usage across the full product lifecycle, using product data and customer feedback to sharpen messaging and identify expansion opportunities • Run ongoing customer and market research, including win/loss analysis, persona development, and buyer journey mapping • Support the US sales team on strategic deals and build repeatable PMM processes as the function scales Requirements • 6–8 years of experience, with at least 3–4 years in B2B product marketing • 0 to 1 product experience, building foundational messaging, enablement, and GTM • Hands-on experience supporting enterprise sales motions, including long sales cycles and multi-stakeholder deals across technical and line-of-business buyers • Track record of turning competitive and user insights into messaging and pitch materials that drive pipeline • Experience launching products and features and driving usage across the product lifecycle • AI literacy: uses AI tools fluently in daily work and can explain AI-driven products credibly to enterprise buyers • Excellent English, written and spoken • Willingness to work regularly overlapping US hours Advantages: • SaaS experience • PLG and/or SLG experience, especially hybrid motions • Background in regulated industries such as insurance, fintech, or legal tech • Experience marketing to US buyers from an Israel-based team