About the Role

We are looking for a Senior React Developer to join an international delivery team supporting a growing technology platform. The ideal candidate will have strong hands-on experience with React and TypeScript, front-end architecture, and the delivery of scalable, accessible, and production-ready applications.

This role requires someone who can take ownership of front-end components from technical design through implementation, testing, deployment, and stabilization, while establishing engineering best practices and mentoring other developers.

Key Responsibilities

Tiger Analytics is a global leader in AI and advanced analytics consulting, empowering Fortune 1000 companies to solve their toughest business challenges. We are on a mission to push the boundaries of what AI can do, providing data-driven certainty for a better tomorrow. Our diverse team of over 6,000 technologists and consultants operates across five continents, building cutting-edge ML and data solutions at scale. Join us to do great work and shape the future of enterprise AI.

Tiger Analytics looking for a Snowflake Administrator - DataOps with 12–15 years of overall IT experience and strong hands-on experience supporting Snowflake administration, DataOps, and DevOps in enterprise environments. The ideal candidate will be responsible for managing and supporting the Snowflake platform, ensuring its availability, security, performance, scalability, and operational stability, while also supporting automation, deployment, monitoring, and DataOps processes.

Key Responsibilities

We are seeking a proactive and customer-focused Application Support Engineer to provide technical support, maintenance, and operational management for business-critical applications. The ideal candidate will ensure high application availability, troubleshoot production issues, coordinate with development and infrastructure teams, and support application deployments while maintaining service level agreements (SLAs).​.

YOU WILL

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. We are hiring a Data Scientist to own the part that comes before the system exists: what question is actually being asked, which method answers it, whether the answer holds up, and how anyone would know.The role is fully remote across Latin America, aligned to your client's working day.

You will not be handed a specification. Azumo has shipped models into production since 2016, and the work here starts with a client who knows what bothers them and does not yet know what to measure. Turning that into a model, a baseline, and a number someone can act on is the job.

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 AI Engineer lane owns production behavior. The Software Engineer lane owns AI-augmented product delivery. This role is the Data Scientist lane, and it owns the question and the method.

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