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:

Tiger Analytics is seeking a highly experienced Lead AI Engineer to lead the end-to-end AI Engineering workstream for the Luma platform. This is a hands-on technical leadership role responsible for driving the architecture, design, and delivery of enterprise-scale Agentic AI solutions while serving as the primary technical interface for the client.

We are looking for a Forward Deployed AI Engineer to build and deploy enterprise GenAI, RAG, Agentic AI, and Knowledge Graph solutions. The role involves working directly with customers, rapidly developing POCs/MVPs, and taking solutions into production.

Requirements

Tiger Analytics is looking for experienced Forward Deployed Engineer (Generative AI) with Gen AI experience to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine Learning, Data Science, and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner.

We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.

Role Overview

The Forward Deployed Engineer (FDE) drives the on-site deployment, integration, and scaling of our enterprise Generative AI solutions. This role embeds directly within customer engineering teams to operationalize Large Language Models (LLMs) and retrieval systems across Google Cloud Platform(GCP).. You will bridge the gap between AI research and production-grade cloud infrastructure.

You will collaborate with cross-functional teams and business partners and will have the opportunity to drive current and future strategy by leveraging your analytical skills as you ensure business value and communicate the results.

Requirements

Technical Requirements

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.

We are looking for a Senior Data Engineer with a strong software engineering background and deep expertise in building modern cloud-based data platforms.

You will be responsible for designing and developing scalable data infrastructure, building reliable data pipelines, and establishing engineering best practices across our data ecosystem. This role is ideal for someone who enjoys solving complex engineering challenges while enabling analytics, machine learning, and product teams with high-quality data.

Role Purpose:

The Cloud DevSecOps Engineer is responsible for designing, implementing, and securing cloud-based infrastructure and CI/CD pipelines. The role ensures seamless automation, robust security integration, and efficient monitoring of systems across OCI and GCP environments to enable secure, scalable, and high-performing applications.

Key Responsibilities:

1. CI/CD Pipeline & DevSecOps

• Design, build, and secure CI/CD pipelines using GitHub Actions.

• Integrate automated security testing (SAST/DAST) using SonarQube and related tools.
• Implement and manage GitOps workflows for continuous delivery using ArgoCD.

2. Cloud Infrastructure & Automation

Location: Santa Ana, California — on-site
Employment type: Full-time
Salary: $172,000 – $220,000

About us

Created.ai is an AI-powered creative platform combining text, image and video generation into production tools for commercial creative work. The platform is operated by eJam, a multi-brand consumer products and technology company.

We are expanding our engineering team with two appointments covering our AI platform infrastructure and our product engineering surface. Both roles carry substantial technical ownership and report directly into engineering leadership.

This position is AI-native by design. Our engineers work with agentic coding tools as a primary part of their daily workflow, which allows a small team to operate at a scope that would conventionally require a much larger one. We are looking for engineers whose judgement, architectural thinking and review discipline scale that leverage rather than being replaced by it.

Role summary

We are seeking a Staff Engineer to take ownership of the AI generation services, provider integrations, billing integrity, tenant security and overall platform reliability underpinning created.ai. The role is Python and GCP-first, with sufficient TypeScript proficiency to trace and modify cross-service contracts.

This is a senior individual contributor position with architectural authority over the platform layer.

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 is looking for a highly experienced Infra Solution Architect to lead enterprise-scale modernization and digital transformation initiatives. The ideal candidate will have deep expertise in AWS and Databricks, extensive experience designing enterprise architecture, and the ability to engage with CXO-level stakeholders to define future-state architectures. This role requires strong consulting, advisory, and technical leadership skills to drive solutioning approaches, and enterprise decision-making.

Requirements

Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best analytics global consulting team in the world.

We are seeking an experienced Data Engineer to join our team, specifically focused on building large-scale ETL/ELT pipelines and analytical architectures within the GCP ecosystem. We are seeking an experienced and dynamic professional to play a key role in assessing, planning, and driving enterprise migration programs across data, applications, and cloud platforms. This role will help clients modernize their technology landscape, optimize legacy systems, and enable scalable, cloud-native architectures aligned with business goals.

Requirements

Location: Remote - Based in the United States

Remote  | Full-time

Compensation: $220K - $300K

Job Description

We are hiring on behalf of our client, an elite team of engineers and cryptographers building the infrastructure behind the next generation of financial systems who are seeking a Senior Infrastructure Engineer. This position is responsible for designing, operating, and scaling the core systems that power a highly secure, high-performance platform.

The successful candidate will build and maintain the infrastructure supporting wallet services, transaction processing, and blockchain integrations. Operating at the intersection of distributed systems, cybersecurity, and cloud infrastructure, this individual will ensure the platform remains exceptionally reliable, secure, and performant. This role extends beyond routine infrastructure operations; it requires a strategic mindset to design resilient architectures, automate complex operations, and continuously optimize deployment, monitoring, and security protocols. The engineer will collaborate closely with cross-functional engineering, product, and security teams to deliver an infrastructure capable of handling intensive, real-world financial workloads.

Key Responsibilities