Level

MongoDB

Technical Services Engineer

MongoDB is hiring a Technical Services Engineer in Mexico City, Mexico. Level rates it ; you can apply on MongoDB.

Level's read on this job

  • Level rates this role Works on AI ●●●○: the daily work is on AI products, without building the model.
  • The posting allows some remote work.
  • Tools and skills the posting cites include LangGraph, Together AI and Docker.
  • Level classifies it as a mid-level role.
  • Level lists 382 other open roles at MongoDB.

AI in this role

Provides technical support and troubleshooting for customers building and operating AI applications on a MongoDB platform.

langgraphtogether-aidockerkubernetesmongodb-atlas
ai-agentstroubleshootingcustomer-supportpythongolangtypescriptai-applications

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 who are based in Mexico City for our hybrid working model.

The role

As a Technical Services Engineer, you will help customers build, deploy, and operate AI applications on a new MongoDB platform. You will investigate issues across application behavior, agent workflows, APIs, cloud infrastructure, and data services, while contributing to the broader MongoDB Technical Services organization as customer needs evolve.

This role is a strong fit for an engineer who enjoys learning new technologies, working directly with customers, and applying structured troubleshooting to complex systems.

What you need

  • Supporting customers and internal stakeholders working with AI applications and agentic workflows
  • Investigating issues involving LangGraph execution, MCP and tool integrations, model-provider behavior, memory, checkpoints, streaming, retries, and timeouts
  • Reading and debugging, Go, Typescript and Python services and agent implementations
  • Troubleshooting Docker and Kubernetes workloads, including deployments, containers, networking, secrets, resource failures, and deployment configuration
  • Using logs, metrics, traces, and application errors to form hypotheses and identify root causes
  • Troubleshooting MongoDB Atlas connectivity, authentication, TLS, network access, indexing, and vector-search issues
  • Reproducing customer problems, developing workarounds, and driving issues through resolution
  • Communicating clearly with customers during complex or high-impact incidents
  • Creating knowledge articles, troubleshooting guides, diagnostic scripts, and reusable runbooks
  • Partnering with Engineering, Product, Security, and other Technical Services teams on escalations and product improvements
  • Contributing to the broader MongoDB database and cloud support cases when needed

Experience level

Typically 5+ years of relevant technical experience, or equivalent demonstrated expertise. We value practical experience and do not require every candidate to have followed the same career path.

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.

MongoDB is an equal opportunities employer.

REQ ID: 3273514739

How we rate this

Technical Services Engineer at MongoDB rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agentsTroubleshootingCustomer SupportPythonGolangTypeScriptAI ApplicationsLangGraph

Questions you could be asked

  1. How do you decide when an AI agent can act on its own versus asking for approval first?
  2. Tell me about a project where troubleshooting was part of your work. What did you do?
  3. Tell me about a project where customer support was part of your work. What did you do?
  4. Tell me about a project where python was part of your work. What did you do?
  5. Tell me about a project where golang was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: AI agents, Troubleshooting, Customer Support, Python, and Golang. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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