SR PLATFORM ENGINEER/ DEVOPS /GenAIOps (Senior) REMOTO ARGENTINA, ID #*****
Location: Anywhere in LATAM
Work Model: 100% Remote
Engagement: Full-time Contractor
Payment: USD
Project: Identity Security / Cybersecurity Platform
Seniority: Senior
144L - Senior DevOps Engineer (AWS/EKS/Terraform/CI/CD) · Remote · LATAM
Location: Anywhere in LATAM
Work Model: 100% Remote
Engagement: Full-time Contractor
Payment: USD
Project: Identity Security / Cybersecurity Platform
Seniority: Senior
English Level: B2 / C1
Get to Know Darwoft
At Darwoft, we build custom software solutions and partner with international companies to create high-impact digital products.
We are a Latin American technology company with a people-first culture, strong professional standards, and a long-term partnership mindset.
We work with distributed teams, complex technical challenges, and clients whose technology has a direct impact on their businesses and users.
About the Project
We are partnering with an innovative cybersecurity company developing a modern Identity Security and Identity Observability platform .
The product enables enterprise security teams to monitor identity activity, identify security gaps, detect suspicious behavior, and reduce identity-related risks across cloud, SaaS, network, and on-premise environments .




Its architecture relies heavily on distributed systems, real-time data processing, cloud-native infrastructure, advanced analytics, and an increasingly AI-driven security roadmap .
As the platform continues to scale, infrastructure reliability, automation, observability, security, and developer productivity are critical engineering priorities.
About the Role
We're looking for a Senior DevOps Engineer to design, automate, operate, and continuously improve the cloud infrastructure and deployment platform supporting a high-scale cybersecurity product.
You'll work primarily with AWS, Kubernetes/EKS, Terraform, Docker, CI/CD, and observability technologies , partnering closely with Software Engineering, QA, Secuation frameworks and iterating on optimization strategies to continuously push the boundaries of inference performance and system efficiency.Distributed Inference Systems: Designing and optimizing high‐performance inference engines using techniques like Tensor Parallelism, Pipeline Parallelism, and Expert Parallelism to handle massive models on GPU clusters.Deep understanding of the math and structure behind Diffusion Models and Vision TransformersUnderstanding of Pruning, Quantization, Flash attention, KV Cache, Speculative Decoding (Eagle) etc.
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