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.
We're looking for a Lead AI Engineer with a background in building AI/ML platform. We are a diverse and talented group of contributors building tools to migrate legacy applications to MongoDB Atlas, our database-as-a-service (DBaaS) offering. This is an exciting opportunity to lead and grow an established team that is undergoing rapid expansion. In this leader-of-leaders position, you will shape the future of the Application Modernization team.
Organizations struggle with legacy applications that lack scalability, resilience, and cloud compatibility. To modernize these systems, many migrate from relational databases to MongoDB—a leading developer data platform for transactional systems. MongoDB's Application Modernization team helps customers through this complex transition with tools like Relational Migrator and is now expanding to include AI-powered code modernization solutions to accelerate the migration process.
We are looking to speak to candidates who are based in the US or Canada for our hybrid working model.
Our ideal candidate will have
4+ years of technical leadership experience managing engineering teams, building platform infrastructure in fast-paced, early-stage environments
2+ years of hands-on experience building and deploying AI agent solutions using frameworks such as AutoGen, CrewAI, LangGraph, TaskWeaver, LangChain, Semantic Kernel, or evaluation suites like OpenAI Evals
Deep understanding of multi-agent coordination, task decomposition, and agent-to-agent communication patterns
Expertise with container orchestration (Kubernetes, Docker) and cloud infrastructure (AWS/GCP/Azure)
Experience with workflow orchestration tools and event-driven architectures
Strong background in building automated testing frameworks, benchmarking systems, and CI/CD pipelines
Experience with performance monitoring, metrics collection, and statistical analysis for system evaluation
Position Expectations
Lead the design and development of a scalable agent orchestrator platform that can deploy, manage, and coordinate multiple AI agents across different use cases
Architect and build a comprehensive benchmarking and evaluation suite for testing agent performance, reliability, and safety across multiple dimensions: accuracy, latency, cost-effectiveness, and robustness
Build robust APIs and SDKs that enable seamless integration of various agent frameworks and models
Establish engineering best practices for code quality, testing, documentation, and deployment
Collaborate closely with ML researchers, product managers, and security teams to define evaluation criteria and platform requirements
Drive technical decision-making and architecture reviews while balancing innovation with system stability
Stay current with the rapidly evolving agent ecosystem and evaluate new frameworks and approaches
Lead and coach a high-performing team of software engineers through the complexities of 0-1 platform development
Partner effectively with engineering and product leaders to align on direction and execution
Create a balanced environment that encourages both iterative improvement and rigorous evaluation
Success Measures
Within the first three months, you will have:
Familiarise yourself with the MongoDB database and aggregation language
Familiarise yourself with the problem space and the domain
Set up software development infrastructure (tech stack, build tools, etc) to enable development using the relevant tech stacks
Started collaborating with your peers and contributed to code reviews
Established deep technical understanding of agent orchestration frameworks, evaluation methodologies, and our existing platform architecture
Within six months, you will have:
Provide design and architectural guidance in extending current software and developing new software
You will be involved in our recruitment of new team members
Identify what mentorship each individual needs to enable them to meet their goals
Delivered core components of the agent orchestrator platform with robust API interfaces and SDK foundations
Within 12 months, you will have:
You will contribute to the vision and growth of our team
You will be involved in our recruitment of new team members
Delivered a comprehensive evaluation suite that provides reliable benchmarking across performance, cost, and safety dimensions
You will be trusted to execute complex projects
Deliver at least one release of our products
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.
MongoDB’s base salary range for this role in the U.S. is:
$137,000 — $270,000 USD
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