Director, Product Management - Data Intelligence Foundation (, MA, United States)

Job Overview Relativity is a leading legal data intelligence company building AI technology that helps organizations organize data, discover the truth, and act on it with confidence. Over two decades, the company has built the most trusted platform in legal data, earning deep relationships with the world's leading law firms, corporations, and government agencies, and managing petabytes of the most sensitive data in existence. That foundation is now being turned into something larger: The AI platform for legal data intelligence. Posting Type Remote/Hybrid Job Overview Relativity is a leading legal data intelligence company building AI technology that helps organizations organize data, discover the truth, and act on it with confidence. Over two decades, the company has built the most trusted platform in legal data, earning deep relationships with the world's leading law firms, corporations, and government agencies, and managing petabytes of the most sensitive data in existence. That foundation is now being turned into something larger: The AI platform for legal data intelligence. The Relativity Intelligence Model is the architecture for that transformation. At its base is the Foundational Layer (Relativity's shared data platform serving all AI applications). Five primitives give AI agents the structure, meaning, and retrieval capability they need to reason over legal data at scale: Files, Ontology, Data Capabilities, Knowledge/Metadata, and Query Plane. Relativity's Data Intelligence Foundation engineering org is building this layer. The product leadership that shapes it, drives adoption across Relativity's product teams, and builds the PM discipline to own it long-term. That's this role. Job Description And Requirements What you'll own The Full PM Layer Across Multiple Engineering Orgs Files / Natives: The storage primitive for legal documents, images, and native files. You define the substrate that makes immutable legal data consistently accessible across every product, partner integration, and AI workflow, with the SLAs, access contracts, and API surface that teams can build on with confidence. The underlying data primitives are the foundation; the degree to which the retrieval layer (Query Plane) matches this structure determines how easily the organization can navigate between slow data and fast data use cases. Ontology / Relationship: The semantic layer of the Relativity Intelligence Model. Ontology encodes meaning: what kinds of things exist in legal data and how they relate, so that AI agents can reason, not just query. You define what Relativity's Ontology becomes: the entities, relationships, and contracts that give every Skill and Agent a shared vocabulary for legal data. Data Capabilities: Reporting, Audit, and internal data infrastructure. The operational backbone that makes the platform observable, auditable, and explainable. These are non-negotiable properties in legal data intelligence use cases. Knowledge / Metadata: The core data model that every product team, customer, and integration partner works with. A unified materialized document layer, consistent across all workspaces, is the mandate. Your roadmap evolves this surface to serve AI application teams as first-class consumers alongside the users who have relied on it for years. Query Plane: One of the most performance-sensitive and strategically important services in the product. The mandate is a unified retrieval pillar with a rich materialized document layer: standardized ingestion APIs independent of data source, hybrid retrieval (lexical vector) with reranking, chunking as a managed capability, and tiered storage (cold/warm/hot). Minimum Qualifications 12 years in product management; 5 years leading platform or infrastructure PM organizations Deep fluency with data platform primitives, including storage systems, metadata layers, knowledge graphs, query engines, or equivalent. You can design an API contract, contribute to engineering scope decisions, and articulate the trade-offs in a data consistency model. Demonstrated ability to manage and build a PM team through hiring, leveling, and establishing product practice for a new domain Bachelor's degree in Business, Computer Science, Engineering, or Design, or comparable work experience Preferred Qualifications Experience building at companies where the data platform is the product, not a supporting system. Snowflake, Databricks, Elastic, MongoDB, Palantir, and similar are strong indicators of the right background. Experience building for AI systems, agents, or ML pipelines as primary consumers. You understand what a model needs from data that a human doesn't, and you design for both. Ways of working Engineering credibility is paramount. You will be in technical discussions with skilled and knowledgeable engineering leaders regularly. You need to be a peer in those conversations, not a relay. Organizational cadence. You establish the operating rhythm for a multi-pillar PM org: the forum structure, planning cadence, and decision frameworks that let the team move with velocity and alignment. When priorities conflict across pillars, you hold the trade-off clearly and resolve it cleanly. Internal GTM ownership. Adoption of the Foundational Layer means every product team at Relativity builds with it. You define how internal teams discover, integrate, and get value from platform services, and you measure it. This is a product strategy job and a change management job simultaneously. Coaching a scaling PM org. You build PM capability, not just PM headcount, leveling people up while running at speed. Cross-functional influence without authority. You don't control the teams that need to adopt what you build. You make the new path clearly better and bring teams along through clarity, evidence, and trust. Directional clarity under ambiguity. Several of these primitives are being defined as the engineering teams build. You make good decisions with incomplete information and update them when required. Legal domain expertise is not required. However, internalizing why defensibility, chain of custody, and auditability are first-class design requirements. Relativity is committed to competitive, fair, and equitable compensation practices. This position is eligible for total compensation which includes a competitive base salary, an annual performance bonus, and long-term incentives. The expected salary range for this role is between following values: $188,000 and $282,000 The final offered salary will be based on several factors, including but not limited to the candidate's depth of experience, skill set, qualifications, and internal pay equity. Hiring at the top end of the range would not be typical, to allow for future meaningful salary growth in this position. J-18808-Ljbffr

Alternatives Business Solutions – Private Equity, Managing Director (Quincy)

Who We Are Looking For State Street is seeking a Managing Director to lead Private Equity Business Solutions and Platform Strategy within Alternatives. This executive leadership role will be responsible for defining and executing the strategic vision for the Private Equity servicing platform, with a particular focus on Investran and the broader ecosystem of applications, workflows, integrations, controls, and operating model components that support the Alternatives business. The successful candidate will serve as the primary business leader responsible for aligning technology capabilities, operational processes, data strategy, and client requirements to create a scalable, efficient, and modern Private Equity servicing platform. This individual will partner closely with Global Delivery, Technology, Product, Operations, Data Strategy, and Client Service teams to drive platform modernization, improve operational resiliency, and establish best practices across the Private Equity organization. What You Will Be Responsible For Platform Strategy & Transformation Leadership Define and maintain the strategic roadmap for the Private Equity technology platform with Investran serving as a foundational component of the operating model. Lead multi-year modernization initiatives focused on application rationalization, automation, workflow digitization, data quality, and platform integration. Establish a future-state operating model that supports scalability, process standardization, and operational excellence across Private Equity servicing functions. Drive the evaluation, prioritization, and execution of strategic business initiatives impacting accounting, investor services, allocations, reporting, workflow management, and data management capabilities. Partner with Technology and Product teams to align investment priorities with business objectives and client requirements. Investran Leadership & Governance Act as the senior business owner and subject matter leader for Investran strategy, governance, and adoption across Private Equity operations. Establish platform standards, governance frameworks, and operating procedures to ensure consistent utilization across regions and service teams. Drive enhancements, integrations, controls, and automation opportunities surrounding Investran and supporting applications. Lead business readiness activities for major platform upgrades, releases, conversions, and new functionality deployments. Partner with operational teams to identify opportunities to reduce manual processing, improve data lineage, and increase straight-through processing. Production Support & Operational Excellence Provide executive oversight for Private Equity platform stability, service delivery effectiveness in collaboration with production support. Establish proactive monitoring, issue management, escalation, and root cause analysis procedures to improve platform resiliency. Collaborate with service delivery, operations, and technology teams to analyze production incidents and work to resolve recurring operational challenges. Develop service metrics and operational reporting that provide transparency into platform health, risk exposure, and performance against objectives. Champion continuous improvement initiatives that strengthen controls, reduce operational risk, and improve user experience. Best Practices, Controls & Model Office Establish and maintain a Private Equity Model Office function focused on process optimization, controls, operational governance, and standardization. Develop best practice frameworks for accounting operations, investor services, workflows, controls, onboarding, reconciliations, and reporting. Proven ability to lead global, cross-functional teams in complex and highly regulated environments. Education & Experience Bachelor's degree in Finance, Accounting, Information Systems, Business Administration, or related field. Advanced degree preferred. 15 years of experience in Alternatives, Asset Servicing, Private Equity, Fund Administration, Financial Technology, or related disciplines. Significant leadership experience overseeing technology strategy, business transformation, or enterprise platform modernization. Demonstrated expertise in Private Markets operating models and large-scale technology implementations. Success Measures The Managing Director Will Be Measured On Advancement of the Private Equity platform strategy and roadmap. Improvement in operational efficiency and automation. Enhanced Investran platform adoption and governance. Reduction of operational risk and production incidents. Increased platform scalability and standardization. Delivery of transformation initiatives on scope, budget, and timeline. Improved client and employee experience. Salary Range $170,000 - $267,500 Annual The range quoted above applies to the role in the primary location specified. If the candidate would ultimately work outside of the primary location above, the applicable range could differ. Employees are eligible to participate in State Street’s comprehensive benefits program, which includes: our retirement savings plan (401K) with company match insurance coverage including basic life, medical, dental, vision, long-term disability, and other optional additional coverages paid-time off including vacation, sick leave, short term disability, and family care responsibilities access to our Employee Assistance Program incentive compensation including eligibility for annual performance-based awards (excluding certain sales roles subject to sales incentive plans) eligibility for certain tax advantaged savings plans For a full overview, visit https://hrportal.ehr.com/statestreet/Home. About State Street Across the globe, institutional investors rely on us to help them manage risk, respond to challenges, and drive performance and profitability. We keep our clients at the heart of everything we do, and smart, engaged employees are essential to our continued success. We are committed to fostering an environment where every employee feels valued and empowered to reach their full potential. As an essential partner in our shared success, you’ll benefit from inclusive development opportunities, flexible work-life support, paid volunteer days, and vibrant employee networks that keep you connected to what matters most. Join us in shaping the future. As an Equal Opportunity Employer, we consider all qualified applicants for all positions without regard to race, creed, color, religion, national origin, ancestry, ethnicity, age, disability, genetic information, sex, sexual orientation, gender identity or expression, citizenship, marital status, domestic partnership or civil union status, familial status, military and veteran status, and other characteristics protected by applicable law. Discover more information on jobs at StateStreet.com/careers Read our CEO Statement Job Application Disclosure It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Job ID: R-796405 J-18808-Ljbffr

Director, AI Platform Reliability (San Francisco)

About Us: We love going to work and think you should too. Our team is dedicated to trust, customer obsession, agility, and striving to be better everyday. These values serve as the foundation of our culture, guiding our actions and driving us towards excellence. We foster a culture of performance and recognition, allowing us to transform growth as we enable our employees to do the best work of their careers. This role is open to candidates based in or near San Francisco, CA. At LogicMonitor, we hire within our Centers of Energy-vibrant locations where our teams connect, collaborate, and innovate. To learn more about life at LogicMonitor, check out our Careers Page . What You'll Do: LogicMonitor® is the AI-first hybrid observability platform powering the next generation of digital infrastructure. LogicMonitor delivers complete visibility and actionable intelligence across on-premises, cloud, and edge environments. By anticipating issues before they strike, optimizing resources in real time, and enabling faster, smarter decisions, LogicMonitor helps IT and business leaders protect margins, accelerate innovation, and deliver exceptional digital experiences without compromise. Our customers love LogicMonitor’s ability to bring cloud and traditional IT together into one view, as seen in minimal churn rates, expansion business, and exciting new customer references. In fact, LogicMonitor has received the highest Net Promoter Score of any IT Infrastructure Management provider. LogicMonitor also boasts high employee satisfaction. We have been certified as a Great Place To Work®, and named one of BuiltIn’s Best Places to Work for the seventh year in a row! We are looking for an accomplished and hands‑on Director of AI Platform Reliability to lead the architecture, development, and operation of highly scalable, distributed software platforms. This leader will be responsible for systems that process hundreds of millions/billions of transactions and events , manage terabytes to petabytes of data , and deliver reliable, low‑latency services to enterprise customers. The ideal candidate combines strong engineering depth in Java, Kafka, distributed systems, and cloud‑native microservices with a demonstrated ability to build and lead high‑performing engineering organizations. This is a strategic leadership role, but it requires a leader who can remain close to the technology, participate in architecture reviews, challenge design decisions, guide teams through complex production problems, and establish the engineering practices required to operate mission‑critical platforms at scale. Here’s a closer look at this key role: Lead and scale multiple engineering teams responsible for high-volume, business‑critical distributed systems and data platforms. Define the technical strategy and architecture for platforms processing hundreds of millions of transactions and terabytes of data. Guide the development of Java‑based microservices, APIs, Kafka streaming pipelines, batch‑processing workflows, and cloud‑native services. Build and evolve scalable data lake and Data Lakehouse platforms supporting real‑time, near‑real‑time, and batch analytics workloads. Establish reliable data ingestion, transformation, storage, governance, lineage, retention, and data‑quality practices across streaming and batch pipelines. Build low‑latency, highly available, fault‑tolerant systems with strong scalability, resiliency, and disaster‑recovery capabilities. Define and own operational SLAs, SLOs, availability targets, recovery objectives, and performance metrics for critical services and data pipelines. Drive capacity planning, load testing, throughput optimization, and improvements to p95 and p99 latency. Ensure effective Kafka design, including partitioning, consumer groups, ordering, schema evolution, replay, and lag management. Establish engineering standards for architecture, coding, testing, security, observability, and production readiness. Partner with Product, Architecture, SRE, Security, Data, and Infrastructure teams to deliver strategic platform initiatives. Strengthen operational excellence through monitoring, incident management, on‑call practices, root‑cause analysis, and continuous reliability improvements. Recruit, mentor, and develop engineering managers, architects, and senior technical leaders. Improve developer productivity, CI/CD automation, deployment safety, and release predictability. Manage technical debt, platform modernization, cloud costs, and long‑term scalability investments. What You’ll Need: 10 years of professional software‑engineering experience, including significant experience building large‑scale distributed systems. Experience leading engineering teams, architects, and staff engineers. Demonstrated success delivering and operating platforms that process hundreds of millions of transactions, requests, or events. Deep technical expertise in Java, JVM performance, concurrency, multithread J-18808-Ljbffr