דרושים Software Engineer Diagnostics ב-Mongodb ב-United States, San Francisco

• Proficient in modern programming languages and techniques
• Eager to impact and envision the technological future of a complex system
• Experienced in developing distributed systems, cloud services and SaaS products
• Experienced in designing and maintaining search platforms or distributed databases is preferred but not required
• Experienced in debugging and profiling multithreaded JVM applications is preferred but not required

• Build and design our integrated search platform, written in Java
• Contribute to two leading open source platforms, MongoDB and Lucene
• Participate in product and design discussions
• Perform code reviews with peers and make recommendations on how to improve our code and software development processes
• Collaborate with other teams including cloud services, database, enterprise tools, drivers and support to coordinate changes or contribute to their projects

• In 3 months, you'll contribute to the improvement of our core "mongoT" repository
• In 6 months, you'll be working on features such as query features or platform improvements
• In 12 months, you'll be building POCs, designing new features, and collaborating with other teams from across the company on complex projects

is a multi-cloud service that allows users to execute complex full text and vector search queries using the . Our users are free to focus on relevance and data retrieval instead of the machinery needed to search data at scale.

This role is based in San Francisco, CA with an in-office or hybrid work model.

• 2+ years of hands-on experience designing, building, testing, and maintaining industrial-strength backend software in a complex codebase
• Experience developing distributed systems and multithreaded applications
• Experience with at least one modern statically typed programming language, and interest in working with Java
• Excellent verbal and written technical communication skills and enthusiasm for collaborating closely with colleagues
• A growth mindset and the desire to learn quickly through taking on challenges, reflecting on outcomes, and incorporating feedback
• A strong sense of ownership over their work, from initial design all the way through maintaining code in production

• Contribute to the design, implementation, and support of projects that improve the scalability of Atlas Search to make using it a seamless experience for even the largest workloads
• Work with a collaborative team that prioritizes sound technical decision-making and building systems that our customers love and that we are proud of as engineers
• Have the opportunity to lead projects and own subsystems
• Provide input on the team’s roadmap and help determine the architecture of our system

• In 3 months you’ll have a solid high-level understanding of what our team does and how we operate. You’ll have contributed to the development of an existing project and completed several small improvements or bug fixes
• In 6 months you’ll be reviewing code and project designs, and be an active participant in team meetings
• In 12 months you’ll have a thorough understanding of the systems our team owns and have led a small project. You’ll have proposed small improvements to our code, product, or team processes

In this role, you’ll have the opportunity to investigate some of the most challenging defects, collaborating with software engineers across the organization as well as senior technical services engineers. In addition, you’ll continually improve our diagnostic processes by contributing to applications and tools that support this mission.

This role can be based out of our San Francisco office or remotely in the western United States.

Please note: Candidates must be a US Person (i.e. U.S. citizen, U.S. national, lawful permanent resident, asylee, or refugee) to fulfill all work responsibilities.

• Work with the Engineering and Technical Services teams to debug and reproduce bug reports from MongoDB users and escalate problems as needed
• Maintain a user-oriented perspective, advise on possible solutions and help MongoDB users understand complex technical issues and options to mitigate or resolve
• Write code to expand our diagnostic toolset, including contributing to electron apps that were developed by our team to investigate diagnostic data

• 3+ years of experience in software development, with a focus on data management systems
• Experience supporting production environments, and/or working directly with end-users to investigate and diagnose technical issues
• Excellent communication skills (both written and verbal) are critical as you will be working with users from all over the world with very diverse backgrounds, as well as with a highly technical engineering team
• Exposure and interest in thorny technical issues central to databases: distributed systems, consensus algorithms, data replication, query optimization, data storage, OS internals, concurrency and scheduling, networking, etc
• Ability to:

• • Quickly grok and clearly synthesize implications of system behavior
  • Contribute to fullstack projects, preferably in Python, Typescript, or Go
  • Read and understand the intent of code and stack traces in many languages, especially C++

• You are comfortable handling tickets with identifiable diagnostic signatures
• You can identify user reported tickets that don’t describe bugs
• You have made contributions to our diagnostic tools

• You are identifying issue patterns and escalating when appropriate
• You can take any issue and work it to completion, either by working it yourself or knowing who and when to pull in additional help
• You have made significant contributions to our diagnostic tools

• You are running a project to improve our diagnostic tools
• You can answer some escalations from our experienced Technical Services Team
• You have a deep understanding in one or more Server components

• Proficient in modern programming languages and techniques
• Eager to impact and envision the technological future of a complex system
• Experienced in developing distributed systems, cloud services and SaaS products
• Experienced in designing and maintaining search platforms or distributed databases is preferred but not required
• Experienced in debugging and profiling multithreaded JVM applications is preferred but not required

• Build and design our integrated search platform, written in Java
• Contribute to two leading open source platforms, MongoDB and Lucene
• Participate in product and design discussions
• Perform code reviews with peers and make recommendations on how to improve our code and software development processes
• Collaborate with other teams including cloud services, database, enterprise tools, drivers and support to coordinate changes or contribute to their projects

• In 3 months, you'll contribute to the improvement of our core "mongoT" repository
• In 6 months, you'll be working on features such as query features or platform improvements
• In 12 months, you'll be building POCs, designing new features, and collaborating with other teams from across the company on complex projects

As a Staff Engineer, you’ll be hands-on with design and implementation, while working with engineers across experience levels to build a robust, scalable system. The focus is on latency, availability, observability, and scalability in a multi-tenant, cloud-native environment.

• Partner with Search Platform and Voyage.ai AI engineers and researchers to productionize state-of-the-art embedding models and rerankers, supporting both batch and real-time inference
• Lead key projects around performance optimization, GPU utilization, autoscaling, and observability for the inference platform
• Design and build components of a multi-tenant inference service that integrates with Atlas Vector Search, driving capabilities for semantic search and hybrid retrieval
• Contribute to platform features like model versioning, safe deployment pipelines, latency-aware routing, and model health monitoring
• Collaborate with peers across ML, infra, and product teams to define architectural patterns and operational practices that support high availability and low latency at scale
• Guide decisions on model serving architecture using tools like vLLM, ONNX Runtime, and container orchestration in Kubernetes

• 8+ years of engineering experience in backend systems, ML infrastructure, or scalable platform development
• Expertise in serving embedding models in production environments
• Strong systems skills in languages like Go, Rust, C++, or Python, and experience profiling and optimizing performance
• Comfortable working on cloud-native distributed systems, with a focus on latency, availability, and observability
• Familiarity with inference runtimes and vector search systems (e.g., Faiss, HNSW, ScaNN)
• Proven ability to collaborate across disciplines and experience levels, from ML researchers to junior engineers
• Experience with high-scale SaaS infrastructure, particularly in multi-tenant environments

• Prior experience working with model teams on inference-optimized architectures
• Background in hybrid retrieval, prompt-based pipelines, or retrieval-augmented generation (RAG)
• Contributions to relevant open-source ML serving or vector search infrastructure

• Be part of shaping the future of AI-native developer experiences on the world’s most popular developer data platform
• Collaborate with ML experts from Voyage.ai to bring cutting-edge research into production at scale
• Solve hard problems in real-time inference, model serving, and semantic retrieval — in a system used by thousands of customers worldwide
• Work in a culture that values mentorship, autonomy, and strong technical craft
• Competitive compensation, equity, and career growth in a hands-on technical leadership role

• Contribute to the design and implementation of customer facing features and products using client and server side Typescript, React, Next.js, and Java
• Own project-level software delivery, including setting and meeting milestones and stakeholder communication
• Participate in product and architecture discussions
• Perform code reviews with peers and make recommendations on how to improve our code and software development processes
• Collaborate with other teams including cloud services, database, enterprise tools, drivers and support to coordinate changes or contribute to their projects
• Work with a talented team of engineers who care deeply about customer problems and implementing great software solutions with the best technologies for the job

• 7+ years of professional experience with application development
• Proficiency in modern programming languages and techniques; preferably Typescript (client and server) and Java
• Proficiency in modern Javascript frameworks; preferably React and Next.js
• Experience developing distributed systems, cloud services and SaaS products
• A history of effectively working with and building consensus among stakeholders across job functions (e.g., product and design)

As a Staff Engineer on the Atlas Data Federation and Archiving team, you will lead the design, optimization, and scalability of our storage and federated query systems. This role focuses on high-performance distributed storage, data lifecycle management, and efficient data retrieval at scale.

This role can be based in New York City, Austin, San Francisco, Seattle, or remotely in the United States.

Storage & Data Processing Performance

• Architect and optimize large-scale storage solutions for federated data access, ensuring efficient retrieval, indexing, and query performance
• Optimize data archival pipelines for high-throughput ingestion, durability, and cost-efficiency
• Improve data tiering and lifecycle policies for moving and querying data efficiently across hot, warm, and cold storage tiers
• Reduce operational costs through intelligent storage layout, compaction strategies, and query execution optimizations

Distributed Query & Execution Engine

• Improve and scale our distributed query execution engine, optimizing it for multi-source federated queries and data lake processing
• Enhance query performance across object storage (e.g., S3, GCS, Azure Blob) by optimizing indexing, partitioning, and compaction techniques
• Implement workload-aware autoscaling for query execution and data processing
• Reduce incident rates by improving system resilience, failover mechanisms, and observability

Technical Leadership & Mentorship

• Guide architectural decisions and lead design reviews across engineering teams
• Mentor engineers in distributed systems, data storage optimization, and operational excellence
• Partner with Product Management to define the technical roadmap for storage and data federation solutions
• Participate in on-call rotation, providing senior oversight for incident response and postmortem retrospectives

• 10+ years experience in software engineering, with a focus on backend and distributed storage systems
• Expertise in large-scale storage systems, such as distributed databases, cloud object storage (S3, Azure Blob, GCS), or data lake technologies (Iceberg, Delta Lake, Hudi, etc.)
• Strong background in designing and optimizing storage layers, indexing, and data lifecycle management
• Experience optimizing query engines for high-volume, low-latency federated data access
• Track record of improving system reliability, observability, and cost-efficiency
• Experience with Kubernetes-based deployment of distributed storage or query systems
• Proficiency in Go or Java (preferred, but not required)
• Deep understanding of query optimizers, storage formats (Parquet, ORC), and indexing strategies
• Experience with disaggregated storage and cloud-native data lake solutions
• Proven ability to lead technical initiatives as an individual contributor while mentoring senior engineers and driving technical excellence within a team.