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Lead AI Engineer, Application Modernization

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Company name
MongoDB
(website)
Annual base salary
$137,000 — $270,000
Posted on SalaryPine

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
  • Proven experience in distributed systems, platform engineering, or developer tooling
  • Expertise with container orchestration (Kubernetes, Docker) and cloud infrastructure (AWS/GCP/Azure)
  • Proficiency in Python and/or JavaScript/TypeScript for building scalable backend services and APIs
  • 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

Life at MongoDB

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: 3263226538

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:$137,000—$270,000 USD
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