Role Overview

We are seeking an experienced Senior AWS EMR Administrator to manage, optimize, and scale our cloud data infrastructure. In this hands-on technical role, you will be responsible for designing, deploying, and maintaining persistent and transient AWS EMR clusters to support large-scale batch data processing pipelines. You will collaborate closely with data engineering teams and leverage Infrastructure as Code (IaC) to ensure reliable, secure, and automated operations across our AWS ecosystem.

Requirements

Azumo builds and operates production AI systems for companies ranging from seed-stage startups to Meta. We are hiring a Senior Security Engineer to own the technical security posture of those systems once they are live: the infrastructure they run on, the pipelines that feed them, and the agents that act on their output. The role is fully remote across Latin America, aligned to your client's working day.

This is not an audit seat. Azumo has shipped production AI since 2016, and the work here is in the systems themselves — hardening infrastructure, closing vulnerabilities, and building the guardrails that keep AI-driven workflows safe in front of real users.

Where this role sits

At Azumo, ownership is split by what gets built: the pipelines, the method behind a decision, the product, and what an AI system does once it's live. Security doesn't work that way. It has to be right across all of them, and that's what this role owns.

Gap or breach, it's yours. If there's a gap, you find it and close it before anyone outside the team does. If there's a breach, you run it: containment, root cause, and the fix that keeps it from happening twice.

Whoever builds the system answers for whether it works. You answer for whether it's safe to run. That split is agreed before the work starts, not reported after.

Senior Security Engineer

Azumo builds and operates production AI systems for companies ranging from seed-stage startups to Meta. We are hiring a Senior Security Engineer to own the technical security posture of those systems once they are live: the infrastructure they run on, the pipelines that feed them, and the agents that act on their output. The role is fully remote across Latin America, aligned to your client's working day.

This is not an audit seat. Azumo has shipped production AI since 2016, and the work here is in the systems themselves — hardening infrastructure, closing vulnerabilities, and building the guardrails that keep AI-driven workflows safe in front of real users.

Where this role sits

At Azumo, ownership is split by what gets built: the pipelines, the method behind a decision, the product, and what an AI system does once it's live. Security doesn't work that way. It has to be right across all of them, and that's what this role owns.

Gap or breach, it's yours. If there's a gap, you find it and close it before anyone outside the team does. If there's a breach, you run it: containment, root cause, and the fix that keeps it from happening twice.

Whoever builds the system answers for whether it works. You answer for whether it's safe to run. That split is agreed before the work starts, not reported after.

What you will build

Cloud DevOps Engineer

Azumo builds and operates production AI systems for companies ranging from seed-stage startups to Meta. We are hiring a Cloud DevOps Engineer to own the infrastructure those systems run on: the clusters, the pipelines that deploy to them, and the monitoring that says whether any of it is healthy. The role is fully remote across Latin America, aligned to your client's working day.

You will not be handed a runbook. Azumo has shipped production infrastructure since 2016, and the work here is in systems that are already live: what breaks, what a cluster costs to run, and what nobody has automated yet because it was always easier to do by hand.

Where this role sits

At Azumo, ownership is split by what gets built: the pipelines, the method behind a decision, the product, and what an AI system does once it's live. This role owns what all of it runs on — clusters, deployment, and the infrastructure those systems depend on to stay up.

A system that is down, a slow query nobody escalates, a cluster that costs more than it should: they are all yours. Recovery first, root cause after, and the change that keeps it from happening again.

What you will build

Azumo builds and operates production AI systems for companies ranging from seed-stage startups to Meta, delivered through small teams working inside each client's environment. We are hiring Forward Deployed Engineers: the engineer embedded in a client's team who owns the system and whether it works, from the first conversation through to whatever breaks after release. The role is fully remote across Latin America, aligned to your client's working day.

Azumo has shipped production AI & Software since 2016, and on these engagements there is no analyst writing the requirement, no QA phase waiting to catch what you missed, and no architect approving your design. Those calls are yours to make and yours to answer for. If you have only ever worked with those roles in place, this is not the seat to start in. We have other openings that probably fit you better.

Where this role sits

Azumo builds and operates production AI systems for companies ranging from seed-stage startups to Meta. We are hiring a Data Engineer to own the layer everything else depends on: ingestion and transformation pipelines, storage and warehouse design, and the retrieval infrastructure that AI systems query. The role is fully remote across Latin America, aligned to your client's working day.

You will not be building pipelines that work until the schema changes. Azumo has shipped production data systems since 2016, and the work here is judged downstream: whether a model can be trained on what you deliver, whether a retrieval query returns the right passage, whether a number survives being questioned by the client.

Where this role sits

Azumo's engineering organization is built around four lanes. The Data Scientist lane owns the question and the method. The AI Engineer lane owns production behavior. The Software Engineer lane owns AI-augmented product delivery. This role is the Data Engineer lane, and it owns pipelines, storage, and the retrieval layer.

One question places the boundary: when the output is wrong, whose problem is it? "The data was missing, stale, or wrong by the time it arrived" is yours."The system did the wrong thing with data that was correct" is the AI Engineer's.

Not quite your profile? Check our other openings:

Azumo builds and operates production AI systems for companies ranging from seed-stage startups to Meta. We are hiring Software Engineers to deliver product software in our clients' stacks, with coding agents as part of how the work gets done rather than as a side experiment. The role is fully remote across Latin America, aligned to your client's working day.

We do not hire by language. Azumo has shipped production software since 2016, and what we test for is whether you can take a problem into a codebase you did not write and leave it better, at a pace a client can plan around. Which language you reach for first tells us where to place you, not whether we want you.

Where this role sits

Azumo's engineering organization is built around four lanes. The Data Engineer lane owns pipelines, storage, and the retrieval layer. The Data Scientist lane owns the question and the method. The AI Engineer lane owns production behavior. This role is the Software Engineer lane, and it owns AI-augmented product delivery.

One question places the boundary: "do you build AI, or do you build with AI?" The AI Engineer answers for what the model does.You answer for what the software does.

Not quite your profile? Check our other openings:

Azumo builds and operates production AI systems for companies ranging from seed-stage startups to Meta. We are hiring a Senior Security Engineer to own the technical security posture of those systems once they are live: the infrastructure they run on, the pipelines that feed them, and the agents that act on their output. The role is fully remote across Latin America, aligned to your client's working day.

You will not be writing policy. Azumo has shipped production AI since 2016, and the work here is in the systems themselves — hardening infrastructure, closing vulnerabilities, and building the guardrails that keep AI-driven workflows safe in front of real users.

Where this role sits

Most engineering organizations split ownership by what's built: pipelines and data infrastructure, the model or the method behind a decision, the product itself, and — once AI systems are live — what they actually do in front of users. Security isn't one more slice next to those. It's the discipline that has to hold inside every one of them, and on any team large enough to carry a dedicated specialist, this is the role that owns it.

Azumo builds and operates production AI systems for companies ranging from seed-stage startups to Meta. We are hiring an AI Engineer to own what those systems do once they are live: retrieval pipelines, tool-using agents, evaluation harnesses, and the guardrails that keep them dependable in front of real users. The role is fully remote across Latin America, aligned to your client's working day.

You will not be building demos. Azumo has shipped production AI since 2016, and the work here starts where the prototype ends, making a system reliable, measurable, and affordable enough to put in front of customers.

Where this role sits

Azumo's engineering organization is built around four lanes. The Data Engineer lane owns pipelines, storage, and the retrieval layer. The Data Scientist lane owns the question and the method. The Software Engineer lane owns AI-augmented product delivery. This role is the AI Engineer lane, and it owns production behavior.

One question places the boundary: when the output is wrong, whose problem is it? "The method was inappropriate" is a Data Scientist question. "The system did the wrong thing with an appropriate method" is yours.

Not quite your profile? Check our other openings:

The Microsoft DevOps Engineer designs, implements and supports secure, resilient and automated Microsoft Azure platforms. The role owns CI/CD pipelines, Infrastructure as Code, cloud operations, monitoring and continuous improvement, working closely with infrastructure, security, application and project teams to accelerate reliable technology delivery.

Key Responsibilities

Azure Cloud Engineering

· Design, deploy and manage Microsoft Azure environments in line with approved architecture and governance standards.

· Support Azure landing zones, networking, compute, storage, backup and disaster recovery services.

· Optimise cloud platform performance, resilience, capacity and cost.

DevOps & Automation

· Design and maintain Azure DevOps CI/CD pipelines using reusable YAML templates.

· Automate infrastructure and application deployment using Terraform, Bicep or ARM templates.

· Manage Git repositories, branching controls, pull requests, artefact versioning and release processes.

· Develop PowerShell, Azure CLI and workflow automation to reduce manual operational effort.

Monitoring & Reliability

· Implement monitoring and alerting with Azure Monitor, Log Analytics and Application Insights.

· Investigate platform and deployment incidents, complete root cause analysis and drive corrective actions.