Jobs
Required skills
Java
AWS
Kubernetes
Go
Terraform
MongoDB
Kafka
The database market is massive and MongoDB is at the forefront of its disruption. At MongoDB, we are transforming how developers build and run applications. Our distributed systems power mission-critical services used by thousands of customers around the globe.
We are looking for a Software Engineer to join the Cloud Core Alerts Platform team, building scalable, fault-tolerant, and highly available systems that process millions of events and alerts in real time.
We are looking to speak to candidates who are based in Dublin for our hybrid working model.
Our domain includes
- Alert Streaming Systems: Real-time alerting pipelines using Apache Flink and Amazon Kinesis, delivering critical insights for Mongo
DB Atlas customers:
-
Event Systems: SOA-based event platforms leveraging gRPC and streaming architectures to power the MongoDB activity feed at scale
-
Communication Systems: Distributed services to deliver alert notifications through multiple channels (email, SMS, Slack, Pager Duty) with reliability and resilience
-
Third-Party Integrations: Securely managing customer credentials and integrating with external observability providers, ensuring encryption at rest and in transit
-
Cross-team Collaboration: Partnering with the broader Customer Observability teams to provide unified telemetry and monitoring experiences
What you’ll do
-
Design and build distributed systems that process millions of events per second with high availability and low latency
-
Lead end-to-end projects from design to production, ensuring scalability, observability, and operational excellence
-
Evolve our streaming alerting and eventing platforms, improving reliability, throughput, and developer experience
-
Collaborate with cross-functional teams to integrate alerting, event, and communication services into the broader customer observability ecosystem
-
Develop secure, multi-tenant integrations with third-party providers, handling sensitive customer credentials safely
-
Champion best practices in distributed systems design, including resilience, scalability, and fault tolerance
-
Mentor and guide other engineers, sharing expertise on distributed architectures and streaming technologies
Who you are
-
Familiar in distributed systems, with at least 2+ years of backend engineering experience (Java, Go, or similar)
-
Familiar with service-oriented architectures (SOA) and inter-service communication using g
RPC or REST:
-
Good understanding of AWS (or other hyperscalers), cloud networking, and infrastructure-as-code patterns
-
Comfortable working in high-scale environments with millions of events and alerts per day
-
A strong communicator, collaborator, and a problem solver
Technologies we use
-
Languages & Frameworks: Java
-
Streaming & Messaging: Apache Flink, Amazon Kinesis, Kafka
-
Service Frameworks: gRPC, Protobuf, REST
-
Datastores: MongoDB, S3
-
Cloud & Infrastructure: AWS, Kubernetes, Terraform
Why Join Us
-
Work on scalable distributed systems that directly impact thousands of global customers
-
Be part of a team modernizing and evolving core observability services for MongoDB Atlas
-
Collaborate with world-class engineers and leaders driving innovation in real-time alerting and event processing
-
Enjoy a supportive, inclusive, and growth-oriented culture
About MongoDB
MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform, the most widely available, globally distributed database on the market, helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.
With offices worldwide and over 60,000 customers, including 75% of the Fortune 100 and AI-native startups, relying on MongoDB for their most important applications, we’re powering the next era of software.
Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us 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 is an equal opportunities employer.
Req ID: 1273394177
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About MongoDB

MongoDB
PublicMongoDB, Inc. is an American software company that develops and provides commercial support for the source-available database engine MongoDB, a database for unstructured data.
5,000+
Employees
New York
Headquarters
$24.0B
Valuation
Reviews
2.6
10 reviews
Work-life balance
3.2
Compensation
3.8
Culture
2.8
Career
2.9
Management
2.4
35%
Recommend to a friend
Pros
Great team environment and culture
Supportive management and mentorship
Good compensation and benefits
Cons
Poor leadership and decision-making
Declining sales culture and difficult quotas
Limited advancement opportunities
Salary Ranges
30 data points
Mid/L4
Senior/L5
Mid/L4 · Manager Marketing Analytics and Operations
1 reports
$114,266
total per year
Base
$99,362
Stock
-
Bonus
-
$114,266
$114,266
Interview experience
8 interviews
Difficulty
3.1
/ 5
Duration
14-28 weeks
Experience
Positive 0%
Neutral 88%
Negative 12%
Interview process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Onsite/Virtual Interviews
5
Final Round
Common questions
Coding/Algorithm
Technical Knowledge
Behavioral/STAR
System Design
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