Role Description As an Engineering Manager at TRM Labs, you will be responsible for executing mission-critical systems and data services that analyze blockchain transaction activity at petabyte scale, ultimately working to build a safer financial system for billions of people. - Lead and develop a team of talented, high-impact engineers, providing cultural, technical, and hands-on leadership. - Provide regular coaching and technical mentorship to your immediate team as well as the broader engineering department. - Take direct responsibility for the quality and delivery of the team's work, and manage the end-to-end availability and performance of critical services. - Drive work based on goals and measurable outcomes that are accountable to KPIs. - Encourage best practices in design and usability, creating scalable engines with thorough documentation and knowledge sharing. - Resolve escalations arising from operations and work with various teams to solve production incidents through to resolution. - Collaborate with management and product teams to plan, estimate, and prioritize roadmap objectives and identify upcoming opportunities and risks. - Build highly reliable data services to integrate with dozens of blockchains. - Develop ETL pipelines that transform and process petabytes of structured and unstructured data in real time. - Design data models for optimal storage and retrieval to support sub-second latency for querying blockchain data. - Deploy and monitor large database clusters that are performant and highly available. - Work cross-functionally with data scientists, backend engineers, and product managers to design and implement new data models to support TRM’s products. Qualifications - Bachelor's degree (or equivalent) in Computer Science or a related field. - 5+ years of experience building distributed system architecture, from whiteboard to production. - Strong programming skills in Python, and SQL or SparkSQL. - Versatility across the entire spectrum of data engineering, including: - Data stores (e.g., ClickHouse, ElasticSearch, Postgres, Redis, and Neo4j) - Data pipeline and workflow orchestration tools (e.g., Airflow, DBT, Luigi, Azkaban, Storm) - Data processing technologies and streaming workflows (e.g., Spark, Kafka, Flink) - Deployment and monitoring infrastructure in public cloud platforms (e.g., Docker, Terraform, Kubernetes, Datadog) - Loading, querying, and transforming large data sets - AI-native mindset: ability to leverage modern AI/ML tools and workflows to accelerate engineering productivity, data processing, and problem solving. Benefits - The estimated base salary range for this role is $220,000 - $240,000. - This role may be eligible to participate in TRM’s equity plan. Company Description TRM Labs provides blockchain analytics and AI solutions to help law enforcement and national security agencies, financial institutions, and cryptocurrency businesses detect, investigate, and disrupt crypto-related fraud and financial crime. TRM is trusted by leading agencies and businesses worldwide who rely on TRM to enable a safer, more secure world for all.

Role Description The Head of Retail Development will focus on the success of 1P and 3P retail channels and serve as a cross-functional partner for 1P Meta Lab stores. You will be responsible for driving innovation—including AI integration—across the retail domain, defining the "Business Brief" for retail locations, and managing the day-to-day retail budget. You will ensure all physical retail initiatives align with hardware product goals and operational standards. - 1P & 3P Channel Leadership: Own the strategic business roadmap and commercial partnership frameworks for all first-party and third-party physical retail footprints globally. - Retail Budget Coordination & Financial Controls: Serve as the primary lead for the retail organization’s annual budget; track and report on OPEX and CAPEX spend for store operations, maintenance, and 1P/3P initiatives; establish and monitor financial controls and performance metrics to track ROI on retail operations and identify cost-saving opportunities, ensuring alignment with Reality Labs’ financial targets. - Business Requirement Definition (Real Estate): Partner with Real Estate to provide the necessary trade-area profiles, store-size parameters, and consumer-flow objectives required to meet hardware sales goals. - Cross-Functional Operational Lead (Store Concepts): Partner with Design and Creative teams to influence store layouts, fixturing, and new store concepts, ensuring these operational needs are ready for handover to execution teams. - Market, Consumer & Portfolio Insights: Leverage AI and advanced analytics to monitor store-level performance and consumer behavior; provide data-driven insights to help the Real Estate team optimize the broader portfolio; surface operational risks and opportunities and recommend adjustments to store formats or 1P/3P strategies based on market trends and consumer behavior. - Internal Stakeholder Management: Build and maintain relationships with internal partners (Legal, Finance, Construction, Facilities) to ensure retail operations are funded, compliant, and operationally supported. - Investment Intake, Governance & Business Cases: Create and own an intake and evaluation framework for new Retail initiatives—standardizing required inputs (costs, risks, benefits), defining approval/stage-gate criteria, and establishing experiment designs with clear pre-launch success metrics; own investment portfolio governance across Retail channels and initiatives by setting prioritization frameworks, running stage gates, and driving reallocation decisions to maximize overall ROI; partner with Finance when changes are material or would drive divergence from the budget POR; establish investment-level business cases and post-investment tracking that quantify unit growth impact and fully loaded cost per unit in collaboration with Finance/Analytics; partner with Data Science to provide incrementality estimates and causal evidence, and packaging those inputs into a clear business case narrative. - Performance Readouts & Decisioning: Deliver channel- and initiative-level performance readouts that clearly articulate returns, tradeoffs, and provide decision-ready recommendations (continue / scale / optimize / stop). Qualifications - BA/BS degree - 12+ years in retail business development, retail operations, or retail financial coordination - 10+ years experience in retail, with significant exposure to managing large-scale retail budgets and physical store scaling - 10+ years experience in tech and/or consumer electronics - Demonstrated expertise in stakeholder and vendor management across complex organizations - Demonstrated experience conveying information clearly and effectively in both written and verbal communication Preferred Qualifications - Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) - Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) - Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies - Bachelor’s degree in Business Management, Finance, or related field - 15+ years of experience in retail development, sales strategy, or business operations, with at least 7 years in an executive leadership role - Experience working in a global retail organization, with an understanding of international markets and cultures - Proven track record of implementing AI or advanced analytics to inform retail business requirements and portfolio performance - Demonstrated knowledge of compliance, budgeting, and financial controls in large-scale retail environments Compensation - $242,000/year to $296,000/year + bonus + equity + benefits

• Lead the design and development of enterprise-grade mobile applications and platform systems. • Architect scalable, stable, and secure mobile frameworks and platforms that support evolving product needs. • Drive major architectural improvements, platform modernization, and codebase overhauls. • Develop and maintain engineering standards, development practices, and reusable architectures across the mobile platform. • Evaluate, select, and implement AI-assisted coding tools and development workflows to improve engineering productivity and quality. • Manage, mentor, and grow a team of mobile engineers. • Foster strong engineering culture through Agile development practices, technical excellence, and collaboration. • Guide mobile engineers through complex technical decisions and ensure delivery of high-quality solutions. • Support hiring, onboarding, and career development of engineers. • Work closely with other technical teams, product, design, and leadership teams to translate requirements into scalable software solutions. • Plan and lead major engineering initiatives including replatforming efforts and large-scale refactors. • Ensure engineering work is delivered using modern Agile methodologies. • Review and approve architecture, designs, and code to maintain quality and performance standards. • Develop and maintain software specifications, system designs, and technical documentation. • Analyze software requirements and propose scalable solutions that integrate with existing systems. • Lead development or modification of internal and third-party applications where required. • Support testing strategies, system validation, and release readiness.

About Eve Eve is redefining legal technology for plaintiff law firms, and we're building the team that will take us there. We help firms handle more cases, recover more for clients, and grow with AI that works across every stage of a case, from intake through resolution. The next generation of great plaintiff firms will be AI-Native, and Eve is how they get there. But what makes Eve different isn't just the product. It's how we build it. If you're someone who takes ownership, stays curious, and wants to build AI that's already changing how law is practiced, this is where you belong. Product-market fit: Eve is trusted by over 1000+ law firms, and we’re growing fast. Backed by top investors: We’ve raised over $160M from world-class partners including Spark Capital, Andreessen Horowitz(A16z), Menlo Ventures, and Lightspeed. Built by a world-class team: Engineers, designers, and operators from places like Scale, Meta, Airbnb, Cruise, Square, Rubrik, and Lyft are building Eve from the ground up. AI-Native from day one: We’re on the bleeding edge of AI, collaborating directly with teams at OpenAI and Anthropic to build best-in-class AI workflows tailored for legal work. Explosive growth: We are growing 2X revenue Quarter over Quarter. What You'll Do: - Build and Scale the Support Engineering Team: Hire, develop, and manage a team of Technical Support Engineers. Build the onboarding program that gets new engineers productive. Create career paths for technical ICs who want to grow without leaving support. Establish a team culture rooted in technical rigor, AI fluency, and customer empathy. - Set the Escalation Quality Standard: Define what a complete, engineering-ready escalation looks like: issue summary, trace logs, verified reproduction steps, document context, and business impact assessment. Close the gap between your best escalations and your average. Make escalation quality a measurable, coached discipline. This is the single most important operational problem to solve in your first 90 days. - Investigate AI Output Quality: A large portion of your team’s work involves investigating why the AI produced a specific output. You’ll build the frameworks and tooling workflows that enable your team to use AI observability platforms to trace model inputs, outputs, and reasoning. You’ll train your team to distinguish between retrieval failures, data ingestion problems, prompt issues, and expected model behavior, then communicate those findings clearly to attorneys who don’t care about your stack. - Build AI-Native Support Operations: Lead the rollout of AI agents for first-touch triage and self-service resolution. Optimize the knowledge base for AI consumption. Define what AI-native support looks like in legal tech, where AI handles routine diagnostic work and your team focuses on complex investigations. - Own the Engineering Relationship: Make engineering trust your team’s triage quality. Your escalations should be so complete that engineers can start working immediately without asking follow-up questions. Ensure all customer-reported issues route through support first, and that support is the fastest, most reliable path to resolution. Build direct relationships with engineering leads. - Build the Measurement System: Establish SLAs, first response time, resolution time, escalation quality scoring, ticket deflection rate, customer satisfaction, incident management, and on-call rotation. Present ticket trends, failure mode patterns, and capacity data to leadership. Your reporting tells leadership what’s actually happening in the product. What We're Looking For: - Technical Support Leadership: You’ve built or significantly scaled a technical support team at a SaaS company. You know how to hire, onboard, coach, and develop support engineers. You’ve managed team performance through metrics. - AI Product Fluency: You understand how AI-powered products work well enough to lead a team investigating AI output quality. You can distinguish between a retrieval failure, a prompt issue, and a data ingestion problem. You don’t need to be an ML engineer, but you need to credibly lead people who debug AI behavior daily. - Escalation Quality Obsession: You’ve personally set the standard for how support communicates with engineering. You know what a complete bug report looks like, and you’ve built systems to ensure your team consistently delivers that standard. - Builder Who Still Debugs: You’ve built support infrastructure before: SOPs, runbooks, knowledge bases, onboarding programs, quality frameworks, AI agent workflows. You also stay close to the technical work. You jump into issues, explore logs, and conduct hands-on testing when needed. - Operational Rigor: You think in systems. SLAs, capacity models, ticket categorization, deflection strategy, CSAT measurement. You build the operating model and hold the team accountable. - Cross-Functional Credibility: Engineering needs to trust that your team’s escalations are complete and accurate. Product needs to trust that your ticket data reflects real patterns. You build that trust by consistently delivering quality. - Customer Empathy: Your customers are plaintiff attorneys, paralegals, and legal operations professionals. They are not developers. They need clear, jargon-free communication and fast resolution. You build a team that communicates at their level. Preferred Qualifications: - 5+ years leading or managing technical support teams at a SaaS company, with experience scaling a team from early stage to operational maturity - Experience supporting AI-powered or ML-driven products, with exposure to LLM observability, evaluation platforms, or AI quality assurance workflows - Track record of building support infrastructure from scratch: SOPs, escalation frameworks, quality scoring, knowledge bases, onboarding programs - Experience deploying AI agents or automation to improve support efficiency and ticket deflection - Familiarity with support tooling ecosystems (ticketing platforms, knowledge management, AI observability tools, bug tracking systems) - Comfort with data analysis: SQL for querying logs, building dashboards, and identifying trends in ticket data - Experience managing the support-engineering relationship, including establishing escalation protocols and quality standards - Understanding of cloud storage integrations (SharePoint, OneDrive, Dropbox) and common failure modes in document-heavy SaaS products - History of developing individual contributors into senior technical roles with clear career progression frameworks - Experience building and maintaining team standards in a fully remote environment Benefits 💰 Competitive Salary & Equity 💹 401(k) Program with Employer Matching ⚕️ Health, Dental, Vision and Life Insurance 🩼 Short Term and Long Term Disability 🚗 Commuter Benefits* 🧑‍💻 Autonomous Work Environment 🖥️ Workplace Setup Reimbursement 🏠 Telecomm Stipend 🏝 Flexible Time Off (FTO) + Holidays 🚀 Quarterly Team Gatherings 🥪 In office Perks* *In office employees only Eve Legal is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, veteran status, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation during the application process, reach out to your recruiter. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.