MongoDB’s mission is to empower innovators to create, transform, and disrupt industries by unleashing the power of software and data. We enable organizations of all sizes to easily build, scale, and run modern applications by helping them modernize legacy workloads, embrace innovation, and unleash AI. Our industry-leading developer data platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available in more than 115 regions across AWS, Google Cloud, and Microsoft Azure. Atlas allows customers to build and run applications anywhere—on premises, or across cloud providers. With offices worldwide and over 175,000 new developers signing up to use MongoDB every month, it’s no wonder that leading organizations, like Samsung and Toyota, trust MongoDB to build next-generation, AI-powered applications.
About the Role
We are seeking a Senior Director of Engineering to lead the development of our Inference Platform within MongoDB. This is a high-impact role where you will drive the technical vision, execution, and growth of a critical component in our AI/ML ecosystem. You will be responsible for building and scaling a world-class team, shaping the future of inference infrastructure, and integrating our cutting-edge models into Atlas, MongoDB’s cloud-managed solution.
We are looking to speak to candidates who are based in Palo Alto or San Francisco for our hybrid working model.
Responsibilities
- Lead and Manage the Voyage Inference Engineering Team – Oversee engineering efforts to design, develop, and scale our inference platform, ensuring high performance, reliability, and efficiency
- Architect and Optimize Large-Scale Inference Pipelines – Work closely with Research Engineers to deploy new embedding models and ensure seamless integration into production environments
- Develop and Scale API Endpoints – Design and maintain the Voyage API to support real-time inference at scale
- Integrate with MongoDB Atlas – Work with cross-functional teams to integrate the inference platform into Atlas, enhancing MongoDB’s AI-powered search and vector capabilities
- Recruit and Build a High-Performance Team – Attract, hire, and mentor top-tier engineering talent, fostering a culture of innovation, collaboration, and technical excellence
- Define Product and Engineering Strategy – Collaborate with product, research, and engineering leaders to define the long-term vision, roadmap, and architecture of the inference platform
- Ensure Operational Excellence – Drive best practices for monitoring, reliability, and performance of ML inference services in production
- Stay Ahead of AI Trends – Keep up with advancements in ML inference, vector search, distributed computing, and hardware acceleration to maintain MongoDB’s leadership in AI-driven search
Requirements
- 10+ years of engineering leadership experience, including managing multiple teams and scaling large, distributed systems
- Proven experience building and maintaining ML inference platforms in production
- Deep expertise in distributed systems, large-scale data processing, and search infrastructure (e.g., Lucene, Elasticsearch, or similar technologies)
- Strong understanding of ML model deployment, vector search, embeddings, and inference optimizations
- Experience working with cloud-native architectures and platforms like AWS, GCP, Azure, and Kubernetes
- Proficiency in high-performance API development and integrating ML pipelines into production systems
- Excellent leadership, strategic thinking, and ability to influence cross-functional stakeholders
- Strong technical background in Python, C++, Java, or Go and experience with ML frameworks like TensorFlow, PyTorch, or ONNX is a plus
- Experience in hiring, mentoring, and scaling world-class engineering teams
Why Join Us?
- Own and lead the development of a core AI/ML platform within MongoDB
- Work with cutting-edge ML and inference technologies to shape the future of AI-driven search
- Collaborate with world-class engineers and researchers on complex, high-scale distributed systems
- Drive technical and product strategy at a high-growth, industry-leading company
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: 1263108638
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:
$185,000—$363,000 USD
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