Backend Engineer - AI/ML Infrastructure

Remote

At CloudGeometry, we're redefining how modern data and AI systems are built. As a leading cloud-native engineering firm, we work with pioneering technology companies to deliver high-impact solutions across infrastructure, machine learning, and intelligent applications.

We are looking for a highly skilled AI Infrastructure Engineers x 5 people to join our growing team supporting large-scale AI/ML systems. This is a hands-on engineering role focused on building scalable, secure, and production-ready infrastructure that powers ML workflows end-to-end—from experimentation to deployment and monitoring.

What You’ll Do

• Design, implement, and maintain robust infrastructure for ML workflows across real-time and batch environments.

• Build and support production-grade model lifecycle systems, including registration, versioning, and deployment workflows.

• Develop APIs and backend services in TypeScript and Python to support model integration and orchestration.

• Manage and optimize infrastructure using AWS and infrastructure-as-code (CDK preferred).

• Work with Databricks MLFlow for end-to-end model management, including asset bundling and serving pipelines.

• Collaborate with cross-functional teams including ML scientists, backend engineers, and DevOps to deliver high-impact features.

• Monitor and improve infrastructure reliability, security, and performance across diverse deployment targets.

• Contribute to CI/CD workflows, container orchestration (Docker, ECS), and automation for ML pipelines.

Why Join CloudGeometry?

You’ll work alongside top-tier engineers across the US, LATAM, and Europe on cutting-edge projects in AI, cloud, and enterprise SaaS. We value deep technical curiosity, strong collaboration, and a bias for action in solving meaningful problems.

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  Seniority Level**

  Mid-Senior level

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  Industry**

  • Software Development

• **

  Employment Type**

  Full-time

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  Job Functions**

  • Engineering

  • Information Technology

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  Skills**

  • Large Language Models (LLM)

  • Software as a Service (SaaS)

  • Databricks Products

  • Python (Programming Language)

  • Infrastructure

  • TypeScript

  • MLflow

  • MLOps

  • Amazon Web Services (AWS)

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Requirements**

What We’re Looking For

• 7+ years in software or infrastructure engineering with proven experience supporting AI/ML systems.

• Deep hands-on experience with AWS services and modern IaC practices (Terraform/CDK).

• Strong backend programming skills in TypeScript and Python.

• Production-level use of MLFlow for model management and deployment.

• Expertise in containerization (Docker), CI/CD automation, and orchestration tools.

• Solid understanding of designing scalable and secure systems in cloud-native environments.

• Strong communication skills, able to bridge gaps between engineering and product stakeholders.

• ⓘ View potential timezone restrictions

  Comfortable in fast-paced, collaborative environments working across time zones.

Nice to Have

• Exposure to LLM infrastructure and frameworks (e.g., DSPy, LangChain).

• Knowledge of LLM performance metrics: latency, cost monitoring, and usage optimization.

• Familiarity with semantic search tools and vector stores (e.g., OpenSearch, Pinecone).

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Benefits**

• Remote anywhere

• Coworking space financial coverage

• Flexible working hours

• B2B with multiple benefits

• Paid days off annually

• Workspace program: 2500$ for work equipment of your choice.

• Paid courses and certifications: example AWS, CKA, ML certifications

• Participation at international conferences: like CNCF Summits, Kubecon, others

Submit Resume

Send us an application to jobs@cloudgeometry.com, and we’ll contact you in shortly.