Engineering Manager, Context (Agentic Search)

Engineering Manager, Search & Context Platform

Notion

WHO WE ARE Notion is the collaborative AI workspace where teams and agents think together. We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. ABOUT THE ROLE Notion's Search & Context Platform is the substrate that powers how 100M+ users and, increasingly, Notion's agents find and reason over the right information. This team owns the search infrastructure and indexing systems powering lexical and semantic retrieval, the platform primitives for managing agent context and memories, and the scalability, performance, security, and enterprise capabilities that make all of it production-grade. Data growth is faster than ever, and the systems that power this need to rapidly evolve to support an order of magnitude growth—both in the volume of content we index and in the load that agents now place on the retrieval layer. As the Engineering Manager for this team, you'll lead a technically deep group of engineers building platform systems used by multiple product teams. Your most important customers are the Search & Context product team and the AI team (building agents on top of these primitives). You'll set the technical direction, product manage the platform scope on behalf of those customers, and make hard tradeoffs to move fast in service of product velocity — while keeping the platform sustainable, reliable, and secure. WHAT YOU'LL ACHIEVE: * Lead a high-performing platform team responsible for search infrastructure (lexical & semantic), indexing (including streaming & batch data pipelines), retrieval (lexical + semantic + hybrid), and the context/memory primitives that power Notion's agents. * Set a clear roadmap that balances foundational platform investments (latency, cost, reliability, scalability, freshness, completeness, security, enterprise readiness) with fast iteration on indexing new entities/features and building new context capabilities for agents. * Operate the platform with a high reliability bar: SLOs, deep observability, on-call health, early-warning signals, and prevention-first incident/post-mortem practices and drive measurable improvements to search and context quality, performance, and reliability for Notion's largest customers and o * Partner and build closely with the Search & Context product team, the AI team, and other consumers of the platform on the right interfaces, capabilities, and commitments. * Staying ahead of the needs of your customer teams by anticipating where the product is going, investing in capacity, capabilities, and primitives and making sure the platform accelerates product velocity. * Build and lead the team through hiring, coaching, feedback, growth, and creating an environment where strong technical ICs do their best work. * Contribute to Notion's broader engineering practices around platform design, reliability, on-call, and AI-era infrastructure. SKILLS YOU'LL NEED TO BRING: * 4+ years of experience leading engineering teams with a track record of shipping high-quality systems in a fast-paced environment. * A technically leaning management style—you stay close to the code and the design, can credibly debate architecture and tradeoffs with senior ICs, and raise the technical bar of your team. * Sufficient depth in search, retrieval, or large-scale data/indexing systems: lexical search (e.g. BM25), semantic search (embeddings, ANN/vector indexes), big data pipelines, hybrid retrieval, ranking, and the surrounding infrastructure. * Experience product managing a platform or infrastructure scope: continuous evaluation technical architecture, SLAs, and a roadmap on behalf of internal customer teams, and making prioritization calls when those customers want different things. * Strong systems judgment around scalability, performance, security, build vs buy and enterprise readiness—you've shipped systems that had to be fast, cheap, secure, and reliable at scale, not just functional. * A bias for making hard tradeoffs to unblock product velocity while protecting the long-term health of the platform; comfortable saying "yes, with these constraints" or "no, here's the better path." * Experience working closely with product and AI teams as customers of a platform—you can speak both languages and translate between them. * High tolerance for ambiguity and rapid change; you enjoy operating in a space where both the product surface (agents, AI) and the underlying technology (retrieval, LLMs) are evolving quickly. NICE TO HAVES: * Experience building agentic or tool-using systems, or platforms that serve LLM-based products. * Familiarity with permissioned, multi-tenant enterprise data—ACL-aware indexing, retrieval, and audit. * Understanding of classic information retrieval metrics, ranking, or applied ML. * Has led teams through rapid scope and priority changes and evolving org boundaries. Notion is committed to providing highly competitive cash compensation, equity, and benefits. The compensation offered for this role will be based on multiple factors such as location, the role’s scope and complexity, and the candidate’s experience and expertise, and may vary from the range provided below. For roles based in San Francisco, the estimated base salary range for this role is $280,000 - $330,000 per year. By clicking “Submit Application”, I understand and agree that Notion and its affiliates and subsidiaries will collect and process my information in accordance with Notion’s Global Recruiting Privacy Policy. #LI-Onsite A NOTE ON AI You don’t need deep AI expertise for every role, but we do expect every Notino to be intellectually curious, drawn to tinkering and discovery, and excited to use AI as a real collaborator in their work. For some roles, AI fluency is a core requirement — when that’s the case, we'll say so explicitly in the qualifications. People who thrive here don’t treat AI as a novelty. They use it to think better, and make their work easier for others to build on. EQUAL OPPORTUNITY & ACCOMMODATIONS We hire talented people from a wide range of backgrounds. If you’re excited about this role but don’t meet every bullet, we still encourage you to apply. Notion is an equal opportunity employer and does not discriminate on the basis of any legally protected characteristic. Consistent with applicable law, we will consider for employment qualified applicants with arrest and conviction records. Notion provides reasonable accommodations during the application process; if you need one, please let your recruiter know. Notion is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristic. Notion considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. Notion is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, please let your recruiter know.

Staff Machine Learning Engineer

Pinterest

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here. The Advertiser and Seller Experience team builds intelligent systems that help Pinterest advertisers and sellers move from insight to action. Our work spans advertiser-facing products such as Ads Manager as well as internal seller productivity tools that help sales teams identify opportunities, prepare customer conversations, troubleshoot campaign performance, and drive advertiser growth. As a Staff Machine Learning Engineer focused on Agentic AI & Recommendations, you will lead the ML strategy and execution for the intelligence layer behind these experiences. You will build recommendation systems, context foundations, and feedback loops that help AI agents understand advertiser and seller goals, surface the right next-best action, and learn from user response over time. This is a high-impact Staff IC role for someone who wants to combine deep recommendation systems expertise with modern agentic AI to shape how Pinterest advertisers and sellers work.   What you’ll do:  * Lead the design and implementation of large-scale recommendation and decisioning systems that power proactive advertiser and seller guidance across Ads Manager, Pinterest Business Assistant, Pinnacle, and sales productivity workflows. * Build ML foundations for a unified context layer and context agent that transforms campaign, account, performance, market, workflow, and interaction data into reusable signals for agentic experiences. * Own recommendation initiatives end-to-end, from problem framing, label and feedback design, feature pipelines, model development, and offline evaluation through production deployment, experimentation, and monitoring. * Develop evaluation and feedback loops that measure recommendation quality, user trust, action rates, business impact, and failure modes, then use those learnings to continuously improve models and agent behavior. * Apply modern ML techniques such as retrieval and ranking, embeddings, personalization, multi-objective optimization, contextual decisioning, and response modeling to business-critical advertiser and seller workflows. * Use AI to accelerate analysis, prototyping, documentation, and experimentation while applying strong judgment, testing, data validation, and review to ensure correctness, reliability, privacy, and customer trust. * Mentor engineers and raise the technical bar for ML development, experimentation rigor, responsible AI usage, and production-quality agentic systems across the organization. What we’re looking for: * 7+ years of experience building and deploying large-scale ML systems in production (e.g., ads ranking, recommendation, Agentic AI, or search), with strong end-to-end ownership from problem scoping through evaluation and experimentation, and solid software engineering skills in at least one modern language (e.g., Python, Java) and large-scale data systems. * Degree in Computer Science, Mathematics, or a related technical field, or equivalent experience. * Strong end-to-end ML ownership, including problem scoping, data and label design, feature engineering, model training, production deployment, offline/online evaluation, experimentation, and monitoring. * Deep understanding of recommendation system architectures such as candidate generation, retrieval, ranking, re-ranking, embeddings, vector search, multi-task learning, calibration, contextual bandits, or reinforcement learning. * Proven Staff-level technical leadership as a hands-on IC, setting technical direction and driving multi-quarter ML and systems roadmaps, including aligning stakeholders on priorities, trade-offs, and execution plans. * Excellent cross-functional communication and collaboration skills, building strong partnerships with product, data science, infra, and partner ML teams to clarify ambiguous problem spaces, co-create solutions, and drive consensus with senior stakeholders. * Experience using AI coding assistants (e.g., Cursor, Claude Code) and LLM-powered productivity tools to accelerate development, experimentation, and data exploration, with a clear approach to validation, data protection, and critical review of AI-assisted work. * Bachelor’s degree in Computer Science, Engineering, a related field or equivalent experience. Relocation Statement: * This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model. In-Office Requirement Statement: *  We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role. * This role will need to be in the office for in-person collaboration 1 day per week and therefore needs to be in a commutable distance from one of the following offices [Seattle or Bay Area]. #LI-REMOTE #LI-DM57 At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise. Information regarding the culture at Pinterest and benefits available for this position can be found here. US based applicants only $189,308—$389,753 USD Our Commitment to Inclusion: Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require a medical or religious accommodation during the job application process, please complete this form for support.   By submitting this application, I certify that all information submitted in my application and throughout the hiring process is true, accurate, and complete to the best of my knowledge. I understand that any false statement, omission, or misrepresentation may disqualify me from employment consideration or result in termination if discovered after hire.

Senior Engineering Manager for Workspace Platform

Databricks

RDQ225R488 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business.  The Workspace Platform team is on an ambitious mission to scale our customer base 100x and support the future of agentic AI workloads. Our goal is to build a unified, consistent, and foundational Shared Platform for the entire Databricks Workspace experience. As a Senior Engineering Manager on the Workspace Platform team, you will lead the development of unified infrastructure powering critical customer-facing capabilities across multiple Databricks products, including Content Discovery (akin to Google Search), Content Organization (akin to Google Drive), Collaborative code editing, and Repository management (akin to Github). This is a high-impact, exciting opportunity to guide a team of ~20 software engineers in creating platform features, intuitive workspace experiences, and partner integrations that are essential to Databricks' expansion and user adoption. The impact you will have: * Strategy & Vision: Define and drive the technical strategy for the Workspace Platform, including building over 16 shared capabilities that underpin the entire Databricks experience. * Execution Ownership: Own the roadmap, execution, and delivery for the platform, ensuring all team deliverables meet the highest standards of quality and timeliness. * Engineering Excellence: Establish and enforce team best practices for engineering excellence, including design reviews, code quality, testing strategies, and performance optimizations for high-volume distributed systems. * Cross-Functional Collaboration: Partner closely with teams across the organization, including those developing vertical product experiences (Lakehouse Platform, SQL Warehouse, AI/BI Dashboards, UC Platform) and core infrastructure, to ensure seamless integration and innovation. What we look for: * Experience: 15+ years of software engineering experience with a strong track record of technical leadership and impact. * Management: 5+ years of engineering management experience, including experience managing other managers. * Scaling: Proven experience scaling engineering teams from 10 to 30+ engineers. * Platform Expertise: Experience leading platform teams and backend developers in a SaaS environment. * Technical Depth: * Experience designing and building scalable distributed systems. * Familiarity with building services on top of containerization technologies. * Expertise in distributed systems, major cloud platforms (AWS, Azure, GCP), and modern web application architectures. * Collaboration: Strong ability to collaborate across product, engineering, and business teams to align technical strategy with core company growth objectives. * Passion: A passion for building and scaling robust, high-performance platforms.     Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles.  Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.   Local Pay Range $217,000—$312,200 USD About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.