Confirm work authorization, visa sponsorship and location requirements with the employer.
About the role
The Search Systems team at MongoDB builds the core infrastructure behind MongoDB Search and Vector Search. Our mission is to make advanced search capabilities feel native to the database, so developers can build powerful, scalable applications without standing up separate systems or compromising transactional performance.
We are the team behind mongot, the indexing and query execution engine that powers Search and Vector Search across MongoDB Atlas and self-managed deployments. Our work sits at the intersection of distributed systems, databases, and search infrastructure. We integrate Apache Lucene with MongoDB using native query operators like $search and $vectorSearch, build asynchronous change-stream-driven indexing pipelines that scale independently from transactional workloads, and support deployments across cloud, on-prem, and hybrid environments. Engineers on this team own meaningful subsystems, influence architectural decisions, and work on core database technology used by developers globally.
We are looking to speak to candidates who are based in San Francisco, CA for our hybrid working model.
WHAT YOU'LL DO
This is a rare opportunity to set the technical direction for one of MongoDB's most strategic investments. You will define the architecture of a self-contained search system that spans Community, Enterprise, and Atlas, while guiding how we integrate AI-native capabilities from Voyage AI. This is not a chance to influence a feature. It is a chance to shape the foundation of how developers everywhere build applications with MongoDB.
Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operati
Own the cross-system data infrastructure layer for MongoDB's next-generation Search and Vector Search capabilities, carrying outcomes that span 6-18 months
Define the technical roadmap for Atlas Search, identifying gaps, proposing solutions, and driving alignment across engineering teams globally
Lead the architecture and evolution of the core mongot and Mongo Management Service infrastructure, making durability, consistency, and scale decisions with conviction
Drive complex, multi-team initiatives by building technical consensus, navigating ambiguity, and setting direction when there is no clean playbook
Serve as a trusted technical partner to leadership on roadmap, architecture, and engineering process, advising rather than just informing
Raise the technical ceiling of the team through mentoring, rigorous code review, and knowledge-sharing that creates leverage beyond your own output
Standardize how engineering teams across the globe contract with one another, reducing coordination costs and increasing execution velocity at scale
WHAT WE'RE LOOKING FOR
Required
10+ years of experience in data management systems or related distributed infrastructure
Deep proficiency in modern programming languages and techniques, with Java fluency preferred
Demonstrable experience designing and operating distributed systems, cloud services, or SaaS products at scale
The ability to reason about systems at the physical layer: data consistency, durability guarantees, concurrency, and failure modes in distributed environments
A track record of operating at Staff or Principal scope: defining technical direction, resolving cross-team ambiguity, and personally championing initiatives from conception to delivery
Preferred (not required)
Experience designing or maintaining search platforms or distributed databases
Experience debugging and profiling multithreaded JVM applications and distributed systems
The profile we hire at this level
Operational Architects. You understand the physical limits of the stack. You can articulate why a system breaks at 100x load, reason about the risks of a dual-write migration strategy, and make data consistency and durability decisions with conviction
Scale-First Thinkers. You identify risks before they surface. You think in migration paths, failure modes, and second-order architectural consequences, not just implementation details
Technical Force Multipliers. You create leverage across teams. You challenge requirements rather than execute them, set technical direction independently, and hold a high bar for architectural clarity whether you are mentoring a struggling engineer or reviewing a design with a principal.
Systems Intuitionists. You connect operational constraints to design decisions in concrete terms. You know why fsync matters. You know how atomic operations behave under contention. You have built systems where these things were not hypothetical.
WHAT SUCCESS LOOKS LIKE
In 3 months: You have developed deep familiarity with the core mongot and Mongo Management Service repos and shipped your first meaningful contribution.
In 6 months: You are driving features that build out new infrastructure for Atlas Search and have identified at least one systemic risk or architectural gap the team had not fully articulated.
In 12 months: You are building POCs, setting technical direction on complex cross-team projects, and actively shaping what the next generation of MongoDB Search looks like.
ABOUT MONGODB
MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the data platform for the AI era, enabling builders to create, transform, and disrupt industries with software. MongoDB’s unified data platform, the most widely available, globally distributed data platform on the market, helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud data platform and is available across AWS, Google Cloud, and Microsoft Azure.
With offices worldwide and over 67,000 customers, including AI-native startups and approximately 75% of the Fortune 100, relying on MongoDB for their most important applications, we’re powering the next era of software.
Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB.
To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!
MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.
MongoDB, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type and makes all hiring decisions without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
Req ID: 3273513566
MongoDB’s base salary range for this role is posted below. Compensation at the time of offer is unique to each candidate and based on a variety of factors such as skill set, experience, qualifications, and work location. Salary is one part of MongoDB’s total compensation and benefits package. Other benefits for eligible employees may include: equity, participation in the employee stock purchase program, flexible paid time off, 20 weeks fully-paid gender-neutral parental leave, fertility and adoption assistance, 401(k) plan, mental health counseling, access to transgender-inclusive health insurance coverage, and health benefits offerings. Please note, the base salary range listed below and the benefits in this paragraph are only applicable to U.S.-based candidates.
MongoDB’s base salary range for this role in the U.S. is: $151,000—$297,000 USD
Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operati
Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operati
Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operati
Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operati
Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operati