דרושים Staff Product Manager – Fp & Planning Tools ב-Mongodb ב-United States, Palo Alto

System Architecture & Development

• Lead the design, configuration, and customization of NetSuite to support R2R and accounting processes (GL, journals, allocations, consolidations, fixed assets, intercompany eliminations)
• Architect scalable NetSuite solutions that integrate seamlessly with upstream and downstream systems (e.g., procurement, billing, expense management, data lake)
• Develop and maintain SuiteScript, SuiteFlow, SuiteTalk (Web Services), and RESTlets to support automation and integrations

Process & Accounting Alignment

• Partner with Finance, Accounting, and Audit teams to translate accounting policies into system-enforced controls within NetSuite
• Act as the primary point of contact for Finance teams including Accounting, Tax, Treasury and RevOps
• Ensure compliance with SOX, GAAP, and audit requirements through configuration of role-based security, approvals, reconciliations, and audit trails
• Optimize financial close processes (journals, reconciliations, accruals, consolidations) to reduce close cycle time
• Build and enhance reporting frameworks (saved searches, financial reports, dashboards) to support accurate and timely financial reporting
• Support compliance and audit requirements through appropriate controls and documentation

Technical Leadership

• Serve as the subject matter expert (SME) for NetSuite R2R and OTC processes, guiding engineers, administrators, and analysts
• Serve as the primary technical advisor for business stakeholders
• Translate business requirements into scalable technical solutions with clear documentation
• Establish engineering best practices in NetSuite development, including coding standards, testing, version control, and deployment
• Drive system performance, scalability, and reliability improvements
• Mentor junior engineers and provide architectural oversight for NetSuite-related initiatives

Integration & Data Management

• Oversee integrations with external systems (e.g., payroll, banking, consolidation tools, CRM platforms like Salesforce, Coupa, Concur)
• Partner with Data Engineering teams to ensure accurate data flow into finance data lake/warehouse for analytics and compliance reporting
• Support data governance, master data management (chart of accounts, dimensions, entity hierarchy) in alignment with accounting standards

Required

• 10+ years of NetSuite development/engineering experience with a focus on General Ledger and accounting modules
• Strong knowledge of OTC and R2R processes including journal entries, close cycle, reconciliations, consolidations, and intercompany accounting
• Proficiency in SuiteScript 1.0/2.0, SuiteFlow, SuiteTalk, REST APIs, and NetSuite integration patterns
• Demonstrated experience implementing system-enforced financial controls and supporting SOX compliance
• Solid understanding of US GAAP and accounting workflows
• Experience with role-based security design, segregation of duties, and audit requirements

Preferred

• Experience with global accounting operations (multi-entity, multi-currency, consolidations)
• Bachelor’s degree in Computer Science, Information Systems, Finance, or related field (or equivalent experience)
• Familiarity with modern finance data stacks and BI/reporting tools
• Prior experience in a high-growth, SaaS or technology company
• Exposure to AI/automation in Finance (e.g., reconciliations, anomaly detection)

Soft Skills

• Strong problem-solving and cross-functional collaboration abilities
• Excellent communication skills, able to translate technical details into business terms
• Leadership mindset with the ability to mentor and influence stakeholders
• Detail-oriented with a commitment to accuracy and compliance

• Impact at Scale: Play a strategic role in modernizing Finance Technology for a growing global organization
• Innovation: Work at the intersection of Finance, Technology, and Compliance to deliver scalable impact
• Cross-Functional Collaboration: Partner with senior leaders in Finance, Procurement, and Technology to deliver systems that enable smarter decisions
• Opportunity to lead technical strategy and influence how core accounting processes are automated and optimized

Req: 3263255986

This role can be based out of our Palo Alto office, or remotely in the United States.

• Conduct cutting-edge research in artificial intelligence, from frontier LLMs to embedding models and rerankers
• Innovate in next-generation information retrieval and LLM agent paradigm
• Collaborate closely with other research scientists and research engineers as well as peers across the organization

• PhD degree in Computer Science or related field
• A track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications in top venues
• Strong background in machine learning, deep learning, and natural language processing
• Experience building complex neural networks for language and visual understanding
• Capable of conducting rigorous empirical studies to validate theoretical results
• Excellent leadership, problem-solving, and communication skills

• Opportunity to work on real-world problems at the cutting edge of AI research
• Opportunity to utilize research vision to innovate the entire company and make real-world impact
• Exposure to the full lifecycle of AI model development, from research to production
• Our compensation (base + equity) for this position is competitive with frontier AI labs

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

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

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

• Design and contribute to our integrated search platform to support ML workloads
• Participate in product and architecture discussions
• Provide thought leadership to continue to scale our architecture to evolve for the needs of tomorrow
• 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

• 10+ years experience delivering large scale systems on production
• Proficient in modern programming languages and techniques preferably Java and Python
• Eager to impact and envision the technological future of a complex system
• Experienced in developing distributed systems, cloud services and SaaS products
• Experience with building Gen AI applications or tools like langchain, llama index is preferred but not required
• Experienced in designing and maintaining search platforms or distributed databases is preferred but not required
• Experienced in debugging and profiling multithreaded JVM applications and distributed applications is preferred but not required

• In three months, you will contribute to search repos to build the foundation for embedding management in MongoDB as well as develop relationships with your team and leaders on other teams
• In six months, you will have delivered a key feature and contribute to design for new ML capabilities in Atlas Search
• In twelve months, you'll be building POCs, designing new features, and collaborating with other Cloud and Server teams on complex projects

This role can be based out of our NYC office or remotely from anywhere in North America.

• Minimum 12 years of experience in programming, debugging, and performance tuning distributed and/or highly concurrent C/C++ software systems
• Strong systems fundamentals, including multi-threaded programming, performance profiling, and expert-level network programming
• Familiarity with database internals or building core components for data processing systems
• Familiarity with observability ecosystem and best practice
• Excellent verbal and written technical communication skills and a strong desire to collaborate with colleagues and mentor engineers
• Excellent time and project management skills including the ability to make realistic assessments of project cost and complexity

• Lead the architecture and implementation of low-level networking components that drive the performance, scalability, cost-efficiency, and resiliency of MongoDB Server
• Design and implement observability improvements that enable MongoDB engineers and customers to quickly and accurately diagnose the root cause of production issues
• Handle networking-related customer escalations from Technical Support team and coach teammates to do the same
• Write production-ready database code in C++, improve the existing code, and mentor their team to write higher quality code
• Own all code the Networking & Observability Team maintains, ensuring it achieves a high standard for quality (including security, durability, availability, and performance) and maintainability
• Write and improve unit and integration tests in C++, Javascript, and Python to demonstrate correctness
• Diagnose test failures, identify bugs in existing code, fix them, and prevent bugs from being introduced in new code
• Investigate the performance impact of code changes that may cause software performance regressions
• Interview candidates for advanced software engineering positions
• Develop and maintain expertise on cutting edge database, networking, and observability developments from industry and academia
• Lead development and project management of some of the largest projects across the company
• Collaborate with stakeholders and engineering teams across the company to jointly work on large initiatives
• Advise Product Management on technical product direction, engineering complexity and inter-project dependencies
• Collaborate with Product Management and Engineering leadership to define product roadmaps

• In the first month, you will have understood the high level architecture of MongoDB networking and observability, and fixed a few bugs
• In three months, you will have contributed to the development in C++ of a project slated for the next major release of MongoDB, and diagnosed and fixed a few customer or testing-reported issues
• In six months, you will have taken on code review responsibilities and are involved in reviewing the design for new features
• In twelve months, you will be leading the development of new features and initiatives, helping to mentor engineers on the team, and using your experience to drive the long-term technical roadmap of the Networking & Observability Team