Technical Instructor: Cloud, DevOps & AI Infrastructure (Live Cohorts)

Read this first: This is a teaching role. You'll spend your days in front of small cohorts — explaining, demonstrating, coaching, and reviewing student work — not building production infrastructure. If your goal is a hands-on DevOps / SRE / Platform engineering job, this isn't it. If you genuinely enjoy helping people "get it," keep reading.

About Transfotech Academy

Transfotech Academy takes learners from beginner to employed, with measurable outcomes at every stage. Built on an outcomes-based education framework and powered by AI, we blend the rigor of a university, the speed of a bootcamp, and the hiring alignment of a corporate academy. Our courses are taught live by hands-on instructors in small cohorts — no pre-recorded content — and every graduate leaves with documented competencies, a verified portfolio, an industry-reviewed capstone, and access to our placement pipeline, where dedicated recruiters actively promote them to employer networks.

What You'll do actually

• Teach live, in small cohorts — Linux, DevOps, cloud, and AI infrastructure

• Design and run hands-on labs, assignments, and real-world deployment scenarios

• Mentor and coach learners one-on-one, not just lecture

• Guide and review capstone projects to an industry standard

• Help learners prepare for interviews and relevant certifications

• Give feedback that turns beginners into hireable practitioners

What You will teach

You don't need to be an expert in every item below, but you should be strong across most and able to pick up the rest quickly.

• Linux, networking & security fundamentals — administration, shell scripting, TCP/IP, DNS, HTTP, load balancing, firewalls

• DevOps workflows & version control — DevOps culture, Git, best practices

• CI/CD — Jenkins, GitLab CI/CD, or similar

• Containers & orchestration — Docker, Kubernetes

• Infrastructure as Code & configuration management — Terraform, Ansible

• Cloud — AWS, Azure, and/or Google Cloud

• Observability — Prometheus, Grafana, logging

• DevSecOps — cloud security, infrastructure hardening

• AI infrastructure & MLOps — GPU workloads, model serving, MLOps concepts, and open-source LLM deployment

What we are looking for

Required

• You've taught, trained, mentored, or coached others in a technical subject — and you enjoyed it

• 5+ years hands-on in DevOps, Cloud, Linux, Platform Engineering, SRE, or MLOps

• Real production experience, not just lab or coursework

• A clear communicator who can make hard things simple

• Comfortable being on camera and in front of a class

• Bachelor's in Computer Science, IT, Engineering, or a related field (or equivalent practical experience)

Nice to have

• Certifications: AWS Solutions Architect or DevOps Engineer, CKA, HashiCorp Terraform Associate, Azure or GCP

• Deeper AI/MLOps experience: Kubeflow, MLflow, Ray, NVIDIA CUDA / AI Enterprise, vector databases, model serving & inference, AI workloads on Kubernetes, model monitoring

Not for you if

• You want to build infrastructure rather than teach it

• You'd rather work solo than explain concepts to beginners

• You can't commit to the cohort schedule