The opportunity
At MongoDB, we're looking for a technically accomplished Solutions Architect who thrives on solving complex problems, understanding how systems work, and helping customers make better architectural decisions. You'll work with established MongoDB customers running production…
What you'll do
Optimize Production Architectures: Analyze MongoDB workloads, query execution, indexing, data models, cluster configurations, and resource utilization. Identify performance bottlenecks, scalability constraints, and cost optimization opportunities
Engineer for Resilience and Scale: Evaluate distributed architectures, replication, sharding, high availability, backup and recovery, and disaster recovery strategies. Help customers understand technical trade-offs and design for evolving production requirements
Think Beyond the Database: Assess how MongoDB interacts with application services, APIs, networking, security, cloud infrastructure, and adjacent technologies. Identify opportunities to simplify architectures, reduce technical debt, and improve operational efficiency
Shape Future-State Architecture: Guide technical discussions around application modernization, cloud-native design, and AI-powered applications. Explore architectural considerations involving Search, Vector Search, RAG, intelligent agents, and their integration with operational data
Lead Technical Discovery and Design: Engage developers, architects, and engineering leaders to investigate complex challenges, analyze technical evidence, assess architectural trade-offs, and develop actionable recommendations. Provide hands-on technical investigation and targeted validation to guide decisions, rather than owning ongoing support cases or implementation projects
Improve How Customers Build and Operate: Look beyond technology to understand development workflows, operational practices, team capabilities, and architectural ownership. Identify opportunities to improve how applications are developed, deployed, and managed
What they're looking for
- Experience with MongoDB, Atlas, NoSQL, or relational database technologies
- Familiarity with query optimization, indexing, data modeling, replication, and database scaling
- Exposure to Kubernetes, Kafka, microservices, APIs, event-driven architectures, or application modernization
- Understanding of AI application patterns, Vector Search, RAG, or agentic systems
