דרושים Senior Software Engineer Inference Platform ב-Mongodb ב-United States, Palo Alto

This role is a cornerstone of our Global VIP Support function, responsible for proactive, high-touch (“white-glove”) technology support for our most senior leaders and their Executive Assistants (EAs).

As the West Coast VIP Support Ambassador, you are the single-threaded owner for executive technology needs in the US Pacific time zone, partnering closely with our NYC (US/Eastern) and Dublin (EMEA) VIP specialists to deliver near 24×5 global coverage.

You will blend senior-level IT support with strong AV and collaboration expertise to protect the most critical executive workflows and events. You will also play a key role in developing and delivering IT training for the EA community, and partnering with Internal Comms and AV on All Hands support. This role requires excellent judgment, calm under pressure, empathy, and the ability to drive complex issues to resolution while maintaining executive trust.

1. White-Glove Incident Response & Resolution

• End-to-end ownership of VIP incidents (P0–P3) during West Coast core hours (typically 9:00–18:00 PT).
• Triage, diagnose, and resolve issues across devices, apps, networking, conferencing, and AV
• Own communication, status updates, and follow-through until full resolution
• P0/P1 live support:
• Join meetings live for shadow checks, audio/video verification, and real-time triage
• Rapidly implement workarounds (room swaps, dial-in bridges, alternate devices) when needed
• PagerDuty participation:
• Participate in the global VIP on-call rotation for after-hours/weekend executive incidents
• Acknowledge and route alerts, escalate per the VIP escalation matrix, and coordinate with NYC/EMEA counterparts
• Smart handoffs for non-VIP traffic:
• Quickly identify non-VIP/general tickets, capture clear diagnostic notes, and hand off to regional L2/IT support
• Remain the escalation point when the issue has executive impact

2. Proactive Care, Stability, & Event / All Hands Support

• Device health and stability:
• Perform regular health checks on executive laptops, backup devices, mobile devices, and conferencing apps
• Ensure OS, security tooling, collaboration apps, and certificates are up to date prior to key events or travel
• High-stakes events & All Hands support:
• Own technical prep for West Coast-based Board meetings, earnings calls, All Hands, customer keynotes, and other VIP events
• Partner with Internal Comms on All Hands execution, including:
• Slide advancement and content playback
• Run-of-show adherence and timing
• Panelist confirmation, speaker tech checks, and backup plans
• Partner with the AV team to provide backstage live support, including green room coordination, backstage comms, and rapid issue triage during broadcasts
• AV/room expertise:
• Maintain a deep understanding of executive rooms and spaces (Zoom Rooms, Teams rooms, DSPs, control systems, cameras, mics)
• Partner with AV Engineering to quickly remediate recurring room issues and ensure executive spaces meet reliability targets
• Automation mindset:
• Identify repeatable VIP support workflows and collaborate with IT/AV engineering to automate (e.g., monitoring alerts, health checks, loaner kit workflows, report generation)

3. Executive Relationship Management, EA Training & Travel Support

• Single-threaded owner for a portfolio of executives/EAs:
• Build trusted relationships with executives and their EAs as their direct technology partner
• Conduct regular check-ins to understand pain points, preferences, upcoming travel, and event calendars
• EA IT training & enablement:
• Design and deliver IT training and development programs for the EA team, focused on collaboration tools, meeting best practices, AV room usage, and VIP playbooks
• Create short guides, office hours, and targeted sessions to help EAs execute complex events and day-to-day workflows with less friction
• Travel & remote support:
• Prepare travel briefs (devices, adapters, connectivity, security, backup options) for executive trips
• Coordinate with hotels, venues, and customer sites on AV and network readiness when required
• Provide occasional on-site support at home offices or offsite locations as needed
• Documentation & knowledge sharing:
• Keep VIP runbooks, playbooks, and checklists current for core tools (Zoom, Teams, WebEx if used, room systems, travel setups)
• Contribute to internal knowledge bases to reduce repeat incidents and enable broader IT teams and EAs to support executives effectively

0–30 Days: Foundational Readiness & Onboarding

• Fully up to speed on the services and technologies we deploy and maintain
• Successfully passed a mock P0 drill, demonstrating calm under pressure and ability to use communication templates
• Complete full runbook, PagerDuty, and Zendesk workflow training
• Shadow two full on-call rotations before taking primary ownership

30–90 Days: Independent Ownership & Proactive Action

• Independently handle day-to-day VIP IT tasks and manage regional handoffs at shift end
• Actively initiate monthly VIP device health checks for assigned executive portfolios
• Fully own triage and resolution for VIP P0/P1 incidents within assigned SLAs (e.g., P0 First Response < 15 min; P1 First Response < 30 min)
• Begin actively developing novel solutions to inefficient processes and problems in your region

90 Days – 1 Year: Efficiency, Strategy & Process Ownership

• Achieve and consistently maintain high weekend SLA compliance (>98%) for PagerDuty coverage
• Lead quarterly EA roundtable/account reviews for your assigned executive portfolio
• Drive a measurable decrease month-over-month in repeat incidents by owning and implementing preventative actions
• Think largely in terms of efficiency, using the skills necessary to execute on automation ideas, and become a trusted technical voice in the organization

Required

• Experience:
• 5+ years in IT end-user support, service desk, or field support
• Meaningful experience (ideally 2+ years) supporting senior leaders, high-touch stakeholders, or VIP users
• Platform & tooling fluency:
• Strong experience with macOS and Windows, common productivity suites (Google Workspace and/or Microsoft 365), and modern endpoint management
• Troubleshooting strength:
• Proven ability to troubleshoot complex, end-to-end issues across devices, networks, identity, and collaboration tools
• Comfortable working in ambiguous, time-sensitive situations and making practical tradeoffs
• Collaboration, AV & live events:
• Hands-on experience with video conferencing platforms (Zoom, Zoom Rooms, Teams, etc.) and meeting room systems
• Experience supporting live events or All Hands (e.g., slide advancement, panelist support, run-of-show execution)
• Familiarity with common AV components (cameras, microphones, DSPs, control panels) and how they interact in a room
• Training & communication:
• Exceptional written and verbal communication skills
• Experience explaining workflows, tools, or best practices to non-technical users, and adapting training material for an EA audience
• Customer mindset:
• Empathetic, patient, and service-oriented; comfortable supporting demanding schedules and high expectations
• Discreet and trustworthy with sensitive information

Preferred

• Experience in a high-growth SaaS, technology, or financial environment supporting senior leadership
• Familiarity with tools such as Okta, JAMF, Meraki, Confluence, Jira, Slack, and modern monitoring/alerting systems (e.g., PagerDuty, Utelogy, Zoom dashboards)
• Experience partnering with AV Engineering, Workplace/Facilities, and Internal Comms teams to deliver high-quality live events and All Hands
• Comfort with light automation or scripting (e.g., Python, PowerShell, or workflow tools) to reduce repetitive manual tasks

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

As a Lead Engineer, Inference Platform, 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. You will also be responsible for guiding the technical direction of the team, mentoring junior engineers, and ensuring the delivery of high-quality, impactful features.

• 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
• Provide technical leadership and mentorship to junior engineers, fostering a culture of technical excellence and continuous improvement within the team

• 8+ years of engineering experience in backend systems, ML infrastructure, or scalable platform development, and the ability to provide technical leadership and guidance to a team of engineers
• 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
• 1+ years of experience serving as TL for a large-scale ML inference or training platform SW project

• 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 infrastructure
• 1+ years of experience in managing a technical team focused on ML inference or training 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

You’ll join the broader Search and AI Platform organization and collaborate with ML researchers and engineers from our Voyage.ai acquisition. Together, we’re building infrastructure for real-time, low-latency, and high-scale inference — fully integrated with Atlas and designed for developer-first experiences.

As a Senior Engineer, you'll focus on building core systems and services that power model inference at scale. You'll own key components of the infrastructure, work across teams to ensure tight integration with Atlas, and contribute to a platform designed for reliability, performance, and ease of use.

• Design and build components of a multi-tenant inference platform integrated directly with MongoDB Atlas, supporting semantic search and hybrid retrieval
• Collaborate with AI engineers and researchers to productionize inference for embedding models and rerankers — enabling both batch and real-time use cases
• Contribute to platform capabilities such as latency-aware routing, model versioning, health monitoring, and observability
• Improve performance, autoscaling, GPU utilization, and resource efficiency in a cloud-native environment
• Work across product, infrastructure, and ML teams to ensure the inference platform meets the scale, reliability, and latency demands of Atlas users
• Gain hands-on experience with tools like vLLM and container orchestration with Kubernetes

• 5+ years of experience building backend or infrastructure systems at scale
• Strong software engineering skills in languages such as Go, Rust, Python, or C++, with an emphasis on performance and reliability
• Experienced in cloud-native architectures, distributed systems, and multi-tenant service design
• Familiar with concepts in ML model serving and inference runtimes, even if not directly deploying models
• Knowledge of vector search systems (e.g., Faiss, HNSW, ScaNN) is a plus
• Comfortable working across functional teams, including ML researchers, backend engineers, and platform teams
• Motivated to work on systems integrated into MongoDB Atlas and used by thousands of developers

• Experience integrating infrastructure with production ML workloads
• Understanding of hybrid retrieval, prompt-driven systems, or retrieval-augmented generation (RAG)
• Contributions to open-source infrastructure for ML serving or search

• Be part of building the AI foundation of the world’s most popular developer data platform
• Collaborate with ML researchers from Voyage.ai to bring novel ideas into scalable systems
• Tackle challenging problems in inference, observability, and distributed infrastructure
• Work in a culture that emphasizes mentorship, ownership, and technical excellence

• 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
• Strong background in machine learning, deep learning, and natural language processing
• Familiarity with training distributed training of neural networks for language and visual understanding

• 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

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

You’ll join the broader Search and AI Platform organization and collaborate with ML researchers and engineers from our Voyage.ai acquisition. Together, we’re building infrastructure for real-time, low-latency, and high-scale inference — fully integrated with Atlas and designed for developer-first experiences.

As a Senior Engineer, you'll focus on building core systems and services that power model inference at scale. You'll own key components of the infrastructure, work across teams to ensure tight integration with Atlas, and contribute to a platform designed for reliability, performance, and ease of use.

• Design and build components of a multi-tenant inference platform integrated directly with MongoDB Atlas, supporting semantic search and hybrid retrieval
• Collaborate with AI engineers and researchers to productionize inference for embedding models and rerankers — enabling both batch and real-time use cases
• Contribute to platform capabilities such as latency-aware routing, model versioning, health monitoring, and observability
• Improve performance, autoscaling, GPU utilization, and resource efficiency in a cloud-native environment.Work across product, infrastructure, and ML teams to ensure the inference platform meets the scale, reliability, and latency demands of Atlas users
• Gain hands-on experience with tools like vLLM and container orchestration with Kubernetes

• 5+ years of experience building backend or infrastructure systems at scale
• Strong software engineering skills in languages such as Go, Rust, Python, or C++, with an emphasis on performance and reliability
• Experienced in cloud-native architectures, distributed systems, and multi-tenant service design
• Familiar with concepts in ML model serving and inference runtimes, even if not directly deploying models
• Knowledge of vector search systems (e.g., Faiss, HNSW, ScaNN) is a plus
• Comfortable working across functional teams, including ML researchers, backend engineers, and platform teams
• Motivated to work on systems integrated into MongoDB Atlas and used by thousands of developers

• Experience integrating infrastructure with production ML workloads
  Understanding of hybrid retrieval, prompt-driven systems, or retrieval-augmented generation (RAG)
  Contributions to open-source infrastructure for ML serving or search

• Be part of building the AI foundation of the world’s most popular developer data platform
• Collaborate with ML researchers from Voyage.ai to bring novel ideas into scalable systems
• Tackle challenging problems in inference, observability, and distributed infrastructure
• Work in a culture that emphasizes mentorship, ownership, and technical excellence