AI Platform Engineer

🔥 0 minutes ago

🇧🇷 Brazil – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🏗️ Platform Engineer

👻 Ghost score 15%

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Modus Create

WebsiteLinkedInAll Job Openings

201 - 500 employees

💼 Consulting

📣 Marketing

📦 Logistics

Consulting • Marketing • Logistics

Modus Create is a digital transformation consulting firm dedicated to helping clients build competitive advantage through digital innovation. Our global team of strategists, designers, and technologists has helped the world’s biggest brands deliver powerful experiences. We specialize in strategic consulting, full lifecycle product development, platform modernization, and digital operations.

📋 Description

• Design, build, and operate secure, scalable cloud platforms for client teams • Work embedded within cross-functional product teams with developers, DevOps engineers, security teams, and product leaders • Reduce deployment friction and improve platform reliability • Own platform deliverables and advise on architecture decisions • Design and implement cloud infrastructure across development, staging, and production • Build and maintain deployment pipelines, CI/CD automation, and infrastructure-as-code • Deploy, operate, and secure AI infrastructure, including LLM serving, vector stores, and agentic systems • Work with AI-assisted development tools and help teams integrate them safely into platforms • Advise on AI deployment patterns and operational best practices in integration reviews • Implement observability systems covering metrics, logging, and tracing • Manage cloud provisioning, configuration, security, reliability, cost, and compliance • Monitor and optimize cloud resources for cost and performance • Collaborate with development, DevOps, security, product, and other cross-capability teams • Troubleshoot platform issues, participate in incident response, and drive improvements • Create runbooks, architecture documentation, and troubleshooting guides • Review infrastructure changes and contribute to architecture standards • Tune systems for latency, throughput, and resource efficiency • Advise leadership on platform strategy and direction • Support teams adopting AI-assisted development tools and ensure safe integration into platform workflows • Monitor model performance, prevent prompt injection attacks, ensure data governance, and scale AI reliably to production

🎯 Requirements

• 3–8 years hands-on platform, infrastructure, DevOps, or cloud engineering • Familiarity with LLM APIs, vector databases, or AI model serving • Familiarity with AI-assisted development tools (GitHub Copilot, Claude, Cursor) • Understanding of AI security: prompt injection, data governance, model monitoring, output validation • Strong proficiency supporting and building in one cloud platform (AWS, Azure, GCP) • Deep experience with infrastructure-as-code (Terraform, CloudFormation, Pulumi, etc.) • Solid understanding of Kubernetes, Docker, and CI/CD pipeline design • Hands-on deployment automation, observability, and incident response • Ability to troubleshoot distributed systems and production issues; comfort with on-call • Clear communication; able to explain technical tradeoffs to technical and non-technical audiences • Scripting proficiency (Python, Bash, Go); Linux/Unix administration fundamentals • Version control (Git), collaboration workflows, and infrastructure automation • Availability for regular working sessions and discovery workshops with client teams • Daily overlap with client business hours • Ability to work independently while collaborating with client and Modus leaders • Ability to document solutions, share learnings, and contribute to internal runbooks • Ability to pair program and collaborate on complex technical problems • Willingness to participate in code and architecture reviews and seek input on designs • Ability to coordinate with security, product, and other teams beyond infrastructure and development

🏖️ Benefits

• Fully remote work environment • Reliable high-speed internet requirement (work arrangement support/requirement) • Opportunities to work with modern cloud platforms, Kubernetes, infrastructure-as-code, and observability • Opportunities to support teams building and deploying AI applications reliably and securely • Opportunities to shape enterprise platform and DevOps best practices • Collaborative, innovative environment with global teams • Opportunities to advise leadership on platform strategy and direction • Opportunities to mentor junior engineers or lead technical design discussions (bonus skill)

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