Currently tracking 11 active AI roles, with 107 new openings in the last 4 weeks. Primary focus: Agent · Engineering. Salary range $118k–$270k (avg $189k).
MongoDB has 32 active AI-related job listings. The majority of these roles are focused on agents, representing 59% of the active listings. Engineering is the top function for these positions. The company is actively hiring for roles related to agent orchestration, model serving, and RAG. Over the last 30 days, MongoDB posted 3 new AI roles, a 25% decrease compared to the prior 30-day period.
MongoDB currently has 34 active AI-related roles in our index. The most common open titles are: Senior Engineering Manager, Code Generation (2), Senior Software Engineer, Forward Deployed AI Engineer (2), Senior Staff Engineer (2), Senior Staff Engineer, AMP (2), Software Engineer, Code Generation (2). Most positions are in Engineering and Product.
MongoDB's active AI hiring is concentrated in: agents (65%), application (15%), serving infrastructure (15%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
MongoDB is hiring AI talent in: United States (14 roles), India (8 roles), Ireland (4 roles), Australia (3 roles).
Job postings at MongoDB most frequently reference: agent orchestration, model serving, rag, code gen, inference infra.
In the past 30 days, MongoDB has posted 5 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Staff Research Scientist Staff Research Scientist at MongoDB's Voyage AI team, focusing on developing next-generation AI models, specifically embedding models and rerankers for information retrieval and RAG. The role involves cutting-edge research in AI, including frontier LLMs and LLM agent paradigms, with a strong emphasis on publication and rigorous empirical studies. | PretrainAgent | 9 |
| Senior Research Scientist, Voyage AI Seeking a Senior Research Scientist to conduct cutting-edge research in AI, focusing on embedding models, rerankers, and next-generation information retrieval and LLM agent paradigms. The role involves developing and innovating AI models for unstructured data search and retrieval, with opportunities for both research and practical deployment. |
| PretrainPost-train |
| 9 |
| Head of AI Platform, GM Head of AI Platform, GM role at MongoDB to lead the development and scaling of a new AI Applications Platform. This intrapreneurial role involves owning the business, vision, and execution of the platform, acting as the CEO of the product line. Responsibilities include defining technical architecture, building a team, scaling the platform, and managing P&L, R&D, and GTM strategy. Requires deep understanding of AI landscape, foundation models, embeddings, vector databases, and experience building scalable cloud/SaaS products and leading large cross-functional organizations. | Agent | 7 |
| Head of Post Sales Technology This role leads the AI strategy and transformation for post-sales customer support, aiming to make it an AI-first, automation-led organization. Responsibilities include defining an AI roadmap, architecting conversational AI platforms, implementing intelligent automation, developing predictive analytics, and owning the support technology stack. The role requires strong technical depth in AI, RAG, and enterprise integration, along with strategic leadership and change management skills. | Agent | 7 |
| Senior Staff Engineer, AMP Senior Staff Engineer to lead the development of a Generative AI-powered platform for modernizing legacy applications. The role involves architecting complex distributed systems, designing orchestration agents, and delivering an enterprise-grade product that balances customer-specific tuning with scalability. Focus on minimizing deployment friction and meeting compliance requirements. | Agent | 7 |
| Senior Staff Engineer, AMP Senior Staff Engineer to lead the development of a Generative AI-powered platform for modernizing legacy applications. The role involves architecting complex distributed systems, designing orchestration agents, and delivering an enterprise-grade product that balances customer-specific tuning with scalability. Focus on minimizing deployment friction and meeting compliance requirements. | Agent | 7 |
| Senior Customer Success Manager Senior Customer Success Manager role at MongoDB, focusing on maximizing customer lifetime value and success for Enterprise accounts. Responsibilities include customer advisory, account management, and internal collaboration to drive retention, revenue, and advocacy. Requires significant experience in technical customer-facing roles and accountability for customer health and revenue. | — | 5 |
| Director, Technology Partners This Director role focuses on executing MongoDB's technology partner strategy, particularly in the AI space, by managing a team of Partner Managers to drive business outcomes and activate partnerships with AI labs, agent frameworks, and developer platforms. The role requires leadership, cross-functional coordination, and technical fluency in AI applications to turn partner relationships into measurable pipeline contribution and co-sell motions. | — | 5 |
| Principal Evangelist This role is for a Principal Evangelist at MongoDB, focused on highlighting builder success and promoting the use of MongoDB's platform, especially in the context of AI. The individual will create content (video, audio, written), engage with the community, and provide feedback to the product team. While the company mentions AI and the role requires active use of AI-assisted coding tools, the core function is not building AI models or systems, but rather promoting a database platform that supports AI development. | — | 5 |
| Principal Business Development Manager, Frontier AI Labs This role focuses on managing relationships with frontier AI model lab partners to ensure MongoDB wins at the infrastructure layer for AI applications. It involves building executive relationships, working with Product on integrations, and driving go-to-market execution for joint initiatives. The role requires deep understanding of AI application architecture and strategic thinking to identify partnership opportunities and drive measurable outcomes. | — | 5 |
| Software Engineer, Data Migration Software Engineer to build tooling for application modernization and data migration to MongoDB, focusing on schema modeling, code generation, and data synchronization. The role involves designing and building components for a generative AI platform, code generation, and migration tools, with a focus on orchestration layers, integration points, and high-performance data systems. Experience with Java, streaming systems, and data-intensive applications is required. | Agent | 5 |
| Senior Technical Product Marketing Manager Senior Technical Product Marketing Manager to lead positioning and messaging for MongoDB Search and Vector Search, focusing on their role as retrieval layers for AI applications and agents. The role requires technical depth in information retrieval and product marketing skills to create differentiated messaging. Experience building or shipping AI-enabled products is a strong advantage. | — | 5 |
| Senior Partner Programs Lead This role focuses on building and scaling a new ISV partner program for MongoDB, specifically targeting horizontal AI-native ISVs and vertical ISVs building AI applications. The Senior Partner Programs Lead will identify, recruit, and activate partners, develop go-to-market strategies, and collaborate cross-functionally to drive adoption and co-sell execution. The role requires business development, commercial acumen, and technical fluency in the context of data platforms and AI applications. | — | 5 |
| Senior Customer Success Manager This role is for a Senior Customer Success Manager at MongoDB, focusing on managing enterprise accounts and maximizing customer lifetime value. The role involves advising customers on complex technical journeys, driving retention and revenue, and collaborating with internal teams. While the company is heavily involved in AI and the role mentions "AI fluency" to enhance customer engagement, the core responsibilities are customer success and account management, not direct AI/ML development. | — | 5 |
| Strategic Customer Success Manager This role is a Strategic Customer Success Manager at MongoDB, focusing on managing and growing relationships with G2000 accounts. The primary responsibility is to act as a trusted technical and business advisor, ensuring customers maximize their investment in MongoDB's platform and achieve their long-term business goals. The role involves driving customer retention, consumption, and executive advocacy, while also collaborating internally to influence the product roadmap. While the company mentions AI and the role uses AI-driven innovation, the core function is customer success and account management, not direct AI/ML development. | — | 5 |
| AI Natives Enterprise Account Executive Enterprise Account Executive focused on selling MongoDB's data platform for AI to AI-native startups in the San Francisco hub. The role involves architecting go-to-market strategies, driving executive engagement, building relationships with founders and VCs, and exceeding revenue targets. Requires 8+ years of quota-carrying field experience selling complex enterprise solutions. | — | 5 |
| Software Engineer, Developer Productivity Software Engineer on the Developer Productivity team at MongoDB, focusing on the Build Team. This role involves improving the reliability, performance, and developer experience of build systems (like Bazel) used to package and ship complex software. The candidate will update tooling, provide internal support, and learn core software development principles for shipping code at scale. While not directly building AI models, the role involves using and tuning AI tools to accelerate development velocity and improve code quality, and the company positions itself as enabling the AI era. | — | 5 |
| Senior Manager, Sales Operations This role leads AI and horizontal platform programs within GTM Operations, focusing on making the global GTM organization more productive, scalable, and AI-enabled. It involves defining use cases, driving cross-functional programs, ensuring adoption of new capabilities, and acting as a GTM process engineer to redesign workflows and apply AI/automation. The role also focuses on AI tool adoption, intake, evaluation, scaling, and upskilling the organization in AI fluency. | — | 5 |
| Strategic Customer Success Manager This role is for a Strategic Customer Success Manager at MongoDB, focusing on helping large enterprise clients maximize their value from MongoDB's platform, particularly in the context of modernizing workloads and enabling AI initiatives. The role involves technical and business advisory, account management, and internal collaboration to drive customer retention, consumption, and advocacy. While the company and its customers are heavily involved in AI, this specific role is customer-facing and consultative, not directly building AI models or infrastructure. | — | 5 |
| Staff Developer Advocate This role is for a Staff Content Engineer on the Builder Relations team, focusing on creating resources and content to help developers integrate MongoDB's data and AI capabilities into their applications. The role involves engaging with the developer community, producing tutorials, articles, and videos, and providing feedback to product teams. While the company is in the AI space and the role mentions AI capabilities and AI-assisted coding tools, the core function is developer advocacy and content creation, not building AI models or systems. | — | 5 |
| Product Manager, Developer Experience Product Manager for Developer Experience at MongoDB, focusing on evolving developer tools to incorporate AI and agentic-driven development, enhancing existing tools with AI experiences, and exploring new AI technologies for working with MongoDB. | — | 5 |
| Senior Customer Success Manager This role is for a Senior Customer Success Manager at MongoDB, focusing on managing enterprise accounts and ensuring customers achieve their business goals using MongoDB's platform, including its AI capabilities. The role involves advising on advanced operational strategies, conducting business reviews, managing customer portfolios for retention and revenue realization, and collaborating internally to influence product roadmaps. While the role mentions 'AI fluency' and the company's focus on AI, the core responsibilities are customer success and account management, not direct AI/ML development. | — | 5 |
| Staff Product Manager - Internal AI Staff Product Manager for Internal AI at MongoDB, focusing on strategy, delivery, and adoption of AI solutions within the enterprise IT landscape. Requires experience in managing AI/ML products at scale and integrating with IT systems. | Ship | 5 |
| Principal, Strategic AI Partnerships This role focuses on building and scaling strategic partnerships with AI infrastructure providers to integrate them with MongoDB's database platform. The goal is to make MongoDB the default data layer for AI applications and agentic workflows, driving technical and go-to-market collaborations. | — | 5 |
| Senior Python Engineer Senior Python Engineer role focused on developing and supporting open-source libraries for MongoDB, with a requirement for practical experience in AI/ML frameworks, LLMs, and agentic tools. The role involves contributing to core drivers, specifications, and collaborating with product teams to shape the roadmap. | — | 5 |
| Senior Python Engineer Senior Python Engineer role focused on building and supporting open-source libraries for MongoDB developers, with a specific emphasis on integrating AI/ML frameworks, large language models, and agentic tools. The role involves contributing to the MongoDB Python drivers and related software, participating in open-source communities, and potentially influencing the roadmap for new user-facing features. | Agent | 5 |
| Senior Director, Data Product Management Senior Director of Data Product Management to own the vision, strategy, and execution of MongoDB's internal data product portfolio, focusing initially on Go-to-Market (GTM) functions. This role involves leading a team of Product Managers and partnering with various data teams to deliver data products like pipelines, datasets, dashboards, APIs, ML models, and self-serve frameworks that support analytics, AI, and business decision-making. The goal is to build a Data-Driven Enterprise with trusted data assets and AI-ready infrastructure. | — | 5 |
| Senior Product Manager - IT Go-to-Market AI Senior Product Manager for IT Go-to-Market organization, owning internal technology products supporting Sales, Marketing, and Revenue Operations. Focus on CRM, lead-to-quote, sales productivity, and marketing automation. Requires 10+ years of PM experience, familiarity with GTM systems, and experience with AI-enabled GTM workflows. | — | 5 |
| Senior Partner Solutions Architect This role is for a Senior Partner Solutions Architect at MongoDB, focusing on guiding customers and partners in designing and building systems using MongoDB's data platform. The role involves technical alignment with the platform and customer needs, acting as a trusted advisor, and supporting sales activities like technical discovery, demos, and proof of value. While the company mentions redefining the database for the AI era and creating AI blueprints, the core responsibilities of this role are pre-sales, solution architecture, and partner relationship management, rather than direct AI/ML model development or deployment. | — | 5 |
| Senior Partner Solutions Architect This role is a Senior Partner Solutions Architect at MongoDB, focusing on guiding customers and partners in designing and building systems using MongoDB's data platform. While the company mentions AI and the role involves working on "AI blueprints" and the "AI era", the core responsibilities are pre-sales technical alignment, solution design, and deal support, rather than directly building or researching AI/ML models or systems. The role leverages AI tools and concepts in the context of MongoDB's platform but is not an AI/ML craft role. | — | 5 |
| AI Staff Developer Advocate AI Developer Advocate to promote MongoDB's AI capabilities, engage with the community, build partnerships with AI companies, create resources, and collaborate with a global team. The role involves empowering developers to integrate AI into their applications, with a focus on vector search and Voyage AI, and building agentic solutions. | Agent | 5 |
| Senior Technical Program Manager, App Modernization The Application Modernization Platform team aids developers in making the shift from relational databases to MongoDB, building toolkits that leverage AI to power seamless transitions. This Senior Technical Program Manager role focuses on owning the successful delivery of complex, cross-functional efforts for Application Modernization, partnering closely with Engineering, Product, and other stakeholders to develop and execute product vision and business objectives. | — | 5 |
| Senior Technical Program Manager, App Modernization This role is for a Senior Technical Program Manager focused on application modernization, helping developers transition from relational databases to MongoDB. The team builds toolkits that leverage AI to power these transitions. The TPM will own the delivery of complex, cross-functional efforts, partnering with Engineering, Product, and other teams to execute the product vision, solve technical challenges, and provide data-driven insights. While the role involves working with AI-powered tools and understanding AI/ML concepts, the core responsibility is program management and delivery, not direct AI/ML model development or research. | — | 5 |
| Senior Staff Engineer, MongoDB Developer Productivity Senior Staff Engineer role focused on enhancing MongoDB's developer productivity ecosystem by integrating analytics assistants and leveraging AI tools to improve developer velocity and efficiency. The role involves driving operational excellence, designing development systems, and providing technical leadership within a large engineering environment. | — | 5 |
| Senior Engineering Manager, Code Generation Senior Engineering Manager for Code Generation team at MongoDB, focusing on leveraging Generative AI to transform legacy applications into modern architectures. The role involves leading a team, driving architectural decisions, and collaborating with product management to deliver a product that solves customer challenges in application transformation. | Ship | 5 |
| Senior Engineering Manager, Code Generation Senior Engineering Manager for a Code Generation team at MongoDB, focused on using GenAI to transform legacy applications into modern architectures. The role involves technical leadership, architectural decision-making, team mentorship, and collaboration with product management to deliver enterprise-grade AI-powered products. | Ship | 5 |
| Senior Software Engineer - Frontend Senior Software Engineer role focused on building customer-facing features for MongoDB Atlas, including AI-powered tools like a chatbot and recommendation system. The role involves leading complex projects, mentoring, and contributing to the technical direction within a cloud engineering group. | — | 5 |
| Senior Staff Enterprise Architect, Q2C & Monetization This role focuses on architecting and modernizing Quote-to-Revenue processes, with a specific emphasis on integrating AI capabilities. The architect will define strategy and lead technical design for monetization platforms, including usage-based billing, and will be responsible for architecting AI-integrated enterprise systems, RAG patterns, vector search, and LLM integration with structured data pipelines. The goal is to enable AI-driven business transformation and improve operational efficiency. | Agent | 5 |
| Senior Staff Enterprise Architect, Data Seeking a Staff Enterprise Architect, Data to lead the strategy, design, and modernization of the enterprise data landscape, focusing on integrating Data Lake and Data Warehouse across multi-cloud platforms. The role will enable self-service data access, natural language query, architect MDM and data lineage for AI models, and evaluate AI tools for data quality and security. Experience with RAG architectures and vector databases is a plus. | Agent | 5 |
| Customer Success Manager Customer Success Manager role at MongoDB, focusing on maximizing customer lifetime value and success for a portfolio of accounts. The role involves advising customers on best practices, managing account plans for customer maturity and retention, and collaborating internally to amplify customer voice and inform product roadmap. The role leverages AI-driven tools to streamline workflows. | — | 5 |
| Software Engineer 3, Atlas Vector Search Software Engineer to build and optimize a vector database on top of MongoDB, focusing on the $vectorSearch aggregation operator for high-dimensional vector queries and performance at scale. | — | 5 |
| Staff Product Marketing Manager Staff Product Marketing Manager responsible for defining marketing strategy for critical product areas and strategic initiatives. This role requires navigating ambiguity, driving GTM strategies, influencing cross-functional teams and senior leadership, and understanding technology fundamentals to effectively market MongoDB's offerings, particularly in the context of generative AI. The role focuses on the business impact and strategic execution of product marketing, not technical implementation. | — | 5 |
| Senior Customer Success Manager Senior Customer Success Manager role at MongoDB, focusing on managing enterprise accounts, driving customer lifetime value, retention, and revenue realization. The role involves advising customers on advanced operational strategies, conducting business reviews, managing account strategy, and collaborating with internal teams to influence product roadmap and ensure customer success with MongoDB's developer data platform, which supports AI initiatives. | — | 5 |
| Senior Software Engineer, Inference Platform Senior Software Engineer to build the next-generation inference platform for embedding models used in semantic search and AI-native experiences within MongoDB Atlas. The role focuses on core systems and services for real-time, low-latency, high-scale inference, collaborating with ML researchers and engineers. | Serve | 5 |
| Senior Data Product Manager, Product Telemetry This role focuses on defining and delivering internal data products, including datasets, reports, APIs, and ML models, to empower Product and Technology teams at MongoDB. The goal is to drive data-driven decisions, enable AI agents, and improve product telemetry and customer insights. The role emphasizes data-as-a-product strategy, stakeholder collaboration, and agile product management within a modern data architecture. | Ship | 5 |
| Senior Manager, Technical Services Engineering This role is for a Senior Manager of Technical Services Engineering at MongoDB. The primary focus is on leading regional teams of Support Engineers who troubleshoot issues related to MongoDB's core database functionality and cloud services. While the role requires an understanding of how AI systems interact with data platforms and how AI can enhance team operations, the core responsibility is managing technical support and customer-facing engineering teams, not directly building or researching AI models. The role emphasizes operational excellence, people management, and deep technical knowledge of database technologies. | — | 5 |
| Senior Pre-Sales Solutions Architect This role is a Senior Pre-Sales Solutions Architect at MongoDB, focusing on guiding customers to design and build systems using MongoDB's data platform. While the role involves understanding and advising on AI/ML projects and RAG architectures, its core function is pre-sales technical consulting and customer success within the broader MongoDB ecosystem, not direct AI/ML model development or deployment. | — | 5 |
| Senior Solutions Architect (Pre-Sales) This role is a Senior Solutions Architect (Pre-Sales) at MongoDB, focusing on helping customers design and build scalable systems using MongoDB's data platform. The role involves customer advising, sales partnership, demand generation, and fostering customer relationships. While the company is redefining the database for the AI era and mentions RAG and AI architectures, the core function of this role is pre-sales technical consulting and solution architecture, not direct AI/ML model development or research. | — | 5 |
| Senior Business Analyst, Technical Services Senior Business Analyst role focused on analyzing Technical Services business processes, pricing, and deal structures to drive insights and support business scaling. The role involves architecting data pipelines, defining reporting needs, and creating dashboards, with a stated interest in leveraging AI technologies. | — | 5 |
| Head of Talent Discovery Head of Talent Discovery at MongoDB, leading a global team to solve complex hiring challenges. This role focuses on strategic sourcing, full-lifecycle support, and leveraging data and AI tools to innovate talent pipelining and drive hiring goals across the organization. The position requires strong leadership, change management, data fluency, and executive influence. | — | 1 |