Technical Services Engineer

MongoDB - Mexico City - original posting ->
Status
Open
Remote policy
Hybrid
Employment type
Not stated
Salary
Not stated
Categories
Technical Support AMER
Tech
awsazuregcpmongodbdockerhelmkubernetesterraformgopythontypescripthybridsoftware
Source
mongodb
First observed
2026-09-08 23:48 UTC
Last seen
2026-10-23 17:56 UTC
Source claims posted
2026-09-08 22:15 UTC
Consecutive misses
0 of 3

What the posting says

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

Quality

Completeness: 65%
Honesty: 90%

Based on 15 observation(s).

Timeline

  1. *
    #645478 2026-09-08 23:48 UTC
    Published
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    #662376 2026-09-09 19:53 UTC
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    #669057 2026-09-10 03:53 UTC
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  5. x
    #669058 2026-09-10 03:53 UTC
    Closed
  6. ^
    #1220168 2026-10-06 22:38 UTC
    Reopened
  7. ~
    #1220169 2026-10-06 22:38 UTC
    Modified
    • Description
      MongoDB Technical Services Engineers use their exceptional problem solving and customer service skills, along with their deep technical...->We are building a new Technical Services capability in Mexico to support a platform that helps customers build, deploy, and operate AI...
    • source_updated_at
      2026-09-08T18:15:35-04:00->2026-10-06T17:20:58-04:00
  8. ~
    #1263921 2026-10-08 22:58 UTC
    Modified
    • source_updated_at
      2026-10-06T17:20:58-04:00->2026-10-08T18:44:35-04:00
  9. ~
    #1267142 2026-10-09 02:59 UTC
    Modified
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      2026-10-08T18:44:35-04:00->2026-10-08T20:14:23-04:00
  10. ~
    #1278580 2026-10-09 16:19 UTC
    Modified
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      2026-10-08T20:14:23-04:00->2026-10-09T10:03:12-04:00
  11. ~
    #1310796 2026-10-13 01:07 UTC
    Modified
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      2026-10-09T10:03:12-04:00->2026-10-12T20:26:05-04:00
  12. ~
    #1323822 2026-10-13 17:08 UTC
    Modified
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      2026-10-12T20:26:05-04:00->2026-10-13T11:42:38-04:00
  13. ~
    #1363707 2026-10-15 17:52 UTC
    Modified
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      2026-10-13T11:42:38-04:00->2026-10-15T12:56:28-04:00
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    #1387450 2026-10-17 01:53 UTC
    Modified
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      2026-10-15T12:56:28-04:00->2026-10-16T17:59:16-04:00
  15. ~
    #1506764 2026-10-23 17:56 UTC
    Modified
    • source_updated_at
      2026-10-16T17:59:16-04:00->2026-10-23T11:31:54-04:00