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About the role
We are building a new Technical Services capability in Mexico to support a platform that helps customers build, deploy, and operate AI applications using MongoDB. This is an early hire on a growing team, and you will have the opportunity to help shape how we support customers, collaborate with Engineering and Product, and build the team’s technical practices from the start.
The platform brings together AI application workflows, orchestration, model and tool integrations, cloud infrastructure, data services, and observability. The support team will work across these layers to help customers troubleshoot complex issues and operate their applications successfully.
We are looking to speak to candidates based in Mexico City for our hybrid working model.
THE ROLE
As a Senior Technical Services Engineer, you will provide technical leadership for customers operating AI applications on a new MongoDB platform. You will own complex investigations across application behavior, agent workflows, APIs, cloud infrastructure, security, and data services, and help shape how Technical Services supports the platform as it scales.
This is a senior individual contributor role where you lead through technical judgment, customer ownership, written communication, and influence across teams.
WHAT YOU’LL DO
Owning complex and high-impact customer investigations involving AI applications and agentic workflows
Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operati
Leading structured investigations, root-cause analysis, and recovery efforts across multiple technical layers
Leading investigations into agent workflows, tool calls, model-provider integrations, memory, checkpoints, streaming, retries, and timeouts
Reading and debugging Go, Typescript, Python services and agent implementations; using logs, metrics, traces, and diagnostic tooling to develop evidence-based conclusions
Troubleshoot Kubernetes and containerized workloads, including deployments, images, secrets, resource failures, and networking
Serving as a technical subject-matter expert for AI application support and related distributed-system issues
Creating and improving troubleshooting methodologies, knowledge articles, diagnostic scripts, and reusable runbooks
Mentoring and coaching engineers in AI fundamentals, cloud-native operations, customer communication, and troubleshooting methodology
Partnering with Engineering, Product, Security, and other Technical Services teams to communicate customer impact and influence product improvements
Reviewing recurring issues and identifying opportunities to improve support processes, tooling, and customer self-service
Contributing to the broader MongoDB database and cloud support cases when needed
EXPERIENCE LEVEL
Typically 8+ years of relevant technical experience, including significant experience troubleshooting production systems, supporting complex customers, or leading technical escalations. Equivalent demonstrated expertise will also be considered.
WHAT YOU’LL BRING
AI and agent platforms: Hands-on experience building or troubleshooting agentic AI applications, including LangGraph, A2A, MCP, tool calling, model-provider integrations, memory, checkpoints, streaming, and human-in-the-loop workflows
Programming and systems troubleshooting: Ability to read and debug Go, TypeScript, and Python services, SDKs, and agent workflows, including asynchronous execution, HTTP clients, retries, and timeouts
Cloud-native platforms: Experience with Docker and Kubernetes, including deployments, containers, networking, secrets, resource management, and deployment troubleshooting
API, identity, and security: Familiarity with REST/JSON APIs, streaming protocols, API keys, OAuth/JWT, RBAC, and service accounts
Observability and incident response: Experience using metrics, events, logs, traces, error monitoring, and alerting to diagnose production issues
Distributed-systems troubleshooting: Experience investigating issues across application, platform, and data layers, communicating clearly with customers, and driving problems through resolution
Bonus Points
Experience with MongoDB, MongoDB Atlas, Atlas Vector Search, Voyage AI or another distributed database
Experience using any cloud services stack such as AWS, Azure or GCP
Experience with Control/Data-plane architecture services
Experience with Terraform, GitHub Actions, CodeBuild, or other CI/CD systems
Experience with Helm, operators, container registries, or advanced Kubernetes networking
Broad awareness of customer workloads and use cases, including performance, availability, and scalability
How you work
Customer-centered problem solving: You have a genuine desire to help people and are motivated by achieving successful customer outcomes
Calm, structured judgment: You can think on your feet, remain calm under pressure, form hypotheses, use evidence, and solve problems in real time
Learning agility: You rapidly build expertise across new technologies, especially AI platforms, distributed systems, and cloud infrastructure
Collaborative ownership: You know when to work independently, when to seek help, and how to provide others with the context needed to move an issue forward
Clear communication: You can explain complex technical issues clearly to customers, engineers, and cross-functional partners
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 data platform for the AI era, enabling builders to create, transform, and disrupt industries with software. MongoDB’s unified data platform, the most widely available, globally distributed data platform 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 data platform and is available across AWS, Google Cloud, and Microsoft Azure.
With offices worldwide and over 67,000 customers, including AI-native startups and approximately 75% of the Fortune 100, 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.
Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operati
Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operati
Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operati
Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operati
Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operati