AI Platform Engineer
Modus Create Costa RicaEst. Est. USD 120,000–170,000 / monthMid
Estimated range based on role, country and industry — not published by the company.
Key requirements
- Python
- Aws
- Azure
- Gcp
- Kubernetes
- Docker
- Terraform
- Ci/Cd
- Linux
AI Platform Engineer
Consultant | Remote
About Us
Modus Create is a digital consulting partner that helps ambitious organizations design, build, and modernize digital products, platforms, and AI-powered experiences. We work shoulder-to-shoulder with client teams to move from idea to production quickly and sustainably, with a clear path to scale.
Founded in 2011, Modus is a global, fully remote team of world-class technologists who thrive in a collaborative, innovative environment. We're a digital product engineering partner for forward-thinking businesses. Our global teams work side-by-side with clients to design, build, and scale custom solutions that achieve real results and lasting change, partnering with industry leaders including AWS, GitHub, and Atlassian.
We were fully remote before it was cool! Recognized as one of the Inc. 5000 Fastest Growing Private Companies for nine years and a top remote work company by FlexJobs, we have helped some of the world's largest brands deliver powerful digital experiences.
Opportunity
We are seeking an experienced Platform Engineer to design, build, and operate secure, scalable cloud platforms that enable client teams to ship faster and with confidence. You'll work embedded within cross-functional product teams—partnering with developers, DevOps engineers, security teams, and product leaders—to reduce deployment friction and improve platform reliability.
As a Platform Engineer (Consultant/Sr. Consultant), you take ownership of your platform deliverables, advise on architecture decisions, and help unblock teams. You design and implement cloud infrastructure, build deployment pipelines, operationalize observability, and contribute to platform security and compliance.Take on greater technical responsibility as you deepen your expertise. You'll work hands-on with AI infrastructure—deploying LLM applications, managing vector databases for RAG systems, securing agentic workflows, and integrating AI services into platform architecture. You'll also support teams adopting AI-assisted development tools (GitHub Copilot, Claude, Cursor) and ensure they're integrated safely into platform workflows. You'll own the operational and security posture of these systems, monitoring model performance, preventing prompt injection attacks, ensuring data governance, and helping teams scale AI reliably to production.
The Platform Engineer will work shoulder-to-shoulder with cross-capability teams to ensure resilient, scalable platform adoption across client environments. You'll also have opportunities to advise leadership on platform strategy and direction—helping shape how organizations modernize their infrastructure and scale their engineering practices.
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
Key Responsibilities & Deliverables
Deploy, operate, and secure AI infrastructure (LLM serving, vector stores, agentic systems)
Work with AI-assisted development tools and help teams integrate them safely into platforms
Advise o
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