MLOps / DevSecOps Engineer – AI Infrastructure Team - 1658

📌 Job Title: Senior MLOps / DevSecOps Engineer – AI Infrastructure Team

Location: Remote from LATAM | Type: Full-time Contractor
Company: Inallmedia.com

🚀 About the Role

As a key member of Inallmedia’s AI Infrastructure Team, you will design, secure, and scale the foundation that powers our generative AI ecosystem—supporting prompts, models, agents, and data pipelines in production.

This role sits at the Copilot layer of the AI architecture, working closely with Prompt Engineers (Operator layer) and AI Governance Specialists to ensure AI systems are secure, observable, auditable, and compliant with frameworks such as NIST AI RMF, ISO/IEC 42001, and SOC 2.

You’ll go beyond traditional DevOps. Your mission is to build infrastructure that is reproducible, governed, and risk-aware, enabling engineering teams to deliver innovation faster—without compromising security or compliance.

🎯 Key ResponsibilitiesInfrastructure & Automation (Copilot Layer)

• Build modular Infrastructure as Code (IaC) for GPU clusters, distributed storage, and secure networking using Terraform, Pulumi, or AWS CDK.

• Deploy and operate GPU-optimized Kubernetes clusters, managing scaling through Cluster Autoscaler or Karpenter.

• Support multi-cloud environments with reproducible, container-based compute for AI training and inference.

CI/CD & Release Management

• Implement multi-stage GitOps pipelines for code, data, models, and prompts using ArgoCD, Flux, or GitHub Actions.

• Design advanced release strategies (canary, blue/green, shadow testing) with rollback triggers based on behavior, security, or cost signals.

• Collaborate with Prompt and AI Dev teams to automate prompt lifecycle deployment and traceability within CI/CD.

Security & Compliance by Design

• Integrate security scanning and policy enforcement into CI/CD (Trivy, Kyverno, Veracode, OPA, SBOM generation).

• Apply Zero-Trust principles, ensuring strong RBAC, encryption, and network segmentation (VPN/VPC).

• Partner with AI Risk & Governance to automate evidence generation, audit logging, and control validation aligned with ISO/IEC 42001 and NIST AI RMF.

• Maintain compliance with SOC 2, ISO/IEC 27034, and internal audit requirements.

Observability & FinOps

• Develop AI-specific observability layers to monitor drift, latency, hallucinations, and token usage.

• Implement cost and performance dashboards using Prometheus, OpenTelemetry, and FinOps exporters.

• Build telemetry pipelines that support both governance analytics and model reliability monitoring.

Collaboration & Cross-Squad Integration

• Work closely with Prompt Engineers, AI Developers, and Governance Specialists to align infrastructure design with compliance and risk frameworks.

• Participate in AI release reviews, helping to define deployment standards for LLMs, copilots, and automated workflows.

• Document IaC and operational runbooks for reproducibility, audit, and handover purposes.

🧠 Ideal Candidate

• 8–10+ years in DevOps, Platform, or MLOps roles, including 5+ years supporting AI/ML infrastructure in production.

• Proven experience deploying LLMs or agentic workflows in secure, regulated environments (finance, healthcare, enterprise SaaS).

• Hands-on knowledge of GPU infrastructure, Kubernetes, IaC, and secure CI/CD automation.

• Strong understanding of AI observability, telemetry, and rollback automation.

• Experience collaborating with AI Risk/Governance teams to enforce traceability and audit-readiness.

• Fluent in English (B2+/C1) with clear communication skills for U.S.-based collaboration.

• Available for 6+ hours overlap with U.S. EST or CST.

🛠️ Recommended StackCategoryTools & FrameworksIaC & ProvisioningTerraform, Pulumi, AWS CDKKubernetes OpsEKS, GKE, AKS, Karpenter, Cluster Autoscaler, Helm, KustomizeCI/CD & GitOpsArgo CD, Flux, GitHub Actions, GitLab CI, Azure DevOpsObservability & FinOpsPrometheus, Grafana, OpenTelemetry, Arize AI, FinOps ExporterSecurity & ComplianceTrivy, Veracode, OWASP ZAP, Kyverno, Snyk, OPA GatekeeperMonitoring & LoggingDatadog, ELK Stack, LokiCloud PlatformsAWS, Azure, GCPReproducibilityDocker, Ansible, VS Code Dev ContainersAI Tooling (Preferred)MLflow, Ray, BentoML, LangSmith, LangChain☁️ Infrastructure & Work Environment

• 100% remote from LATAM

• Secure access via VPN, Okta, or Azure AD

• Fully containerized, cloud-native environments (AWS/Azure/GCP)

• Collaboration via GitHub Enterprise, Jira, and Slack/Teams

• Work closely with Prompt Engineers, Governance, and Data Engineering squads

🔍 What We’re Looking For

✅ Engineers who implement, not only design infrastructure.
✅ Professionals who understand how governance connects with DevOps.
✅ Builders who ensure every deployment is observable, auditable, and reversible.

🚫 Not a fit if you:

• Only handle standard infrastructure without AI or model workloads.

• Lack experience with rollback, telemetry, or model release management.

• Have never worked in compliance-heavy or U.S.-based enterprise environments.

👣 Next Steps

If you’re ready to build the backbone of AI deployment with a focus on security, observability, and governance, we’d love to hear from you.
👉 Apply now and join Inallmedia’s AI Stewardship Squad, where engineering and compliance meet to power responsible AI at scale.

📌 Job Title: Senior MLOps / DevSecOps Engineer – AI Infrastructure Team

Location: Remote from LATAM | Type: Full-time Contractor
Company: Inallmedia.com

🚀 About the Role

As part of Inallmedia's AI Infrastructure Team, you’ll be responsible for designing, securing, and scaling the technical foundation that supports the deployment of generative AI models, prompts, and data pipelines in production.

This role goes beyond traditional DevOps or MLOps work. You’ll build systems that are secure by design, reproducible at scale, traceable for audit, and compliant with modern AI governance frameworks (e.g., NIST AI RMF, ISO/IEC 42001, SOC 2). You’ll enable engineering and governance teams to move faster—without compromising security or control.

You’ll own infrastructure, CI/CD, observability, and deployment strategies for LLMs and AI-powered workflows, supporting a multi-model environment in high-compliance contexts.

🎯 Key Responsibilities

• Build modular Infrastructure as Code (IaC) for GPU clusters, distributed storage, and secure networking (Terraform, Pulumi, AWS CDK).

• Deploy and operate GPU-optimized Kubernetes clusters using Cluster Autoscaler or Karpenter; manage node pools and cost-effective scaling.

• Implement multi-stage GitOps pipelines for code, data, models, and prompts using ArgoCD, Flux, GitHub Actions, or Azure DevOps.

• Design advanced release strategies (canary, blue/green, shadow testing) with rollback triggers based on behavior, security, or cost anomalies.

• Integrate security scanning into CI/CD pipelines (OWASP ZAP, Trivy, Veracode, Snyk); implement OPA/Kyverno policy gates and SBOM generation.

• Build AI-specific observability layers to monitor model drift, latency, hallucinations, token usage, and budget burn.

• Collaborate with the AI Risk & Governance team to automate evidence generation, audit logging, and traceability aligned to ISO/IEC 42001 and NIST AI RMF.

• Maintain compliance with standards like SOC 2, ISO/IEC 27034, and internal security audits.

• Support reproducible compute environments in both cloud and hybrid architectures (Terraform, AWS CDK, containers).

🧠 Ideal Candidate

• 8–10+ years in DevOps, Platform Engineering, or MLOps roles, including 5+ years with AI/ML infrastructure in production.

• Proven track record deploying LLMs or model pipelines in secure, regulated environments (finance, healthcare, enterprise).

• Deep experience with GPU infrastructure, Kubernetes, IaC, and secure CI/CD automation.

• Hands-on mindset with a strong sense of ownership, precision, and ability to interface with compliance and governance teams.

• Clear communication and experience working with U.S.-based teams, in cross-functional squads.

• Fluent in English (written/oral); Spanish is a plus.

• Available for 6+ hours of overlap with U.S. EST or CST time zones.

🛠️ Recommended StackCategoryTools & FrameworksIaC & ProvisioningTerraform, AWS CDK, PulumiKubernetes OpsEKS, GKE, AKS, Karpenter, Cluster Autoscaler, Helm, KustomizeCI/CD & GitOpsArgo CD, Flux, GitHub Actions, GitLab CI, Azure DevOpsObservabilityPrometheus, Grafana, OpenTelemetry, Arize AI, FinOps ExporterSecurity & ComplianceTrivy, Veracode, OWASP ZAP, Kyverno, Snyk, OPA GatekeeperMonitoring & LoggingDatadog, ELK Stack, LokiCloud PlatformsAWS, Azure, GCPReproducibilityDocker, Ansible, VS Code Dev Containers, cloud-based IDEsML Frameworks (Nice)MLflow, Ray, BentoML, LangSmith, LangChain☁️ Infrastructure & Environment

• Remote-first across LATAM

• GitHub Enterprise, Jira, Slack/Teams

• Secure access via VPN and Okta or Azure AD

• Fully containerized and cloud-based dev environments

• Collaboration with Prompt Engineers, AI Risk/Governance, and Data Engineering

🔍 What We’re Not Looking For

• Infra engineers without real-world experience supporting LLMs or model pipelines in production

• DevOps profiles who only focus on infrastructure and lack understanding of AI-specific risk/observability

• Candidates with no experience implementing release rollback, prompt lifecycle, or telemetry traceability

• Engineers who haven’t worked with U.S.-based companies or in compliance-heavy environments

👣 Next Steps

If you're ready to build the infrastructure backbone for real-world AI deployments, let’s talk.
We’re looking for hands-on builders with a governance mindset.

👉 Apply now and help shape the infrastructure layer of our AI Stewardship Squad.