Algotale (Safe Security)-DevOps Engineer

About Algotale (Client-Safe Security)

Algotale is a data-centric IT consulting and staffing firm dedicated to reshaping industries through AI, machine learning, and cutting-edge cloud solutions. We pride ourselves on building resilient digital infrastructures and empowering businesses to unlock the true potential of their data. As we scale our AI-driven platforms, we are looking for a Senior DevOps Engineer with an SRE mindset to ensure our systems are fast, reliable, and infinitely scalable.

The Role

We are seeking an expert

DevOps/Site Reliability Engineer

to bridge the gap between development and operations. You will be the architect of our cloud infrastructure on AWS, ensuring that our Kubernetes-orchestrated services run with high availability and efficiency. With over 5 years of experience, you will lead the charge in automation, performance tuning, and infrastructure security.

Key Responsibilities

Infrastructure Orchestration

Own, scale, and optimize multi-region production workloads using

Kubernetes (EKS)

. Design Helm charts and maintain infrastructure as code (IaC) using Terraform.

Data & AI Pipelines Support

Architect and monitor resilient, high-throughput message queues and event-driven architectures utilizing

Apache Kafka

and

AWS SQS

to ingest real-time cybersecurity telemetry for our AI modeling engines.

Automation & Scripting

Write clean, production-grade automation scripts and internal tools using

Python

to eliminate manual interventions, handle auto-scaling, and manage data life cycles.

CI/CD Deployment

Build, secure, and maintain automated CI/CD deployment pipelines to safely ship code multiple times a day to Dev, Staging, and Production environments with zero downtime.

Security & Compliance (DevSecOps)

Implement shift-left security practices. Integrate automated vulnerability scanning (SAST/DAST, container scanning) into build pipelines, manage IAM roles, network isolation, and encryption to meet stringent enterprise compliance standards (SOC2, ISO).

Observability & Reliability

Set up robust logging, metrics monitoring, and alerting frameworks (e.g., Prometheus, Grafana, ELK, Datadog) to proactively guarantee 99.9% uptime for our core AI SaaS platform.

Requirement Specification (Qualifications & Experience)

Technical Must-Haves

Experience

Minimum 5 years of dedicated experience in DevOps / Site Reliability Engineering roles within a SaaS production environment.

Containerization & Orchestration

Advanced, hands-on production experience managing

Kubernetes

clusters at scale (cluster upgrades, network policies, namespace isolation, ingress control).

Cloud Expertise

Strong command over

AWS

core services (EC2, VPC, EKS, IAM, RDS, S3, Route53, CloudWatch).

Advanced Scripting

Strong proficiency in

Python

for automation, system utilities, and cloud engineering tasks (beyond basic bash scripting).

Streaming & Messaging Tech

Proven track record of configuring, tuning, and troubleshooting distributed messaging queues, specifically

Apache Kafka

or

AWS SQS

under heavy data loads.

Infrastructure as Code

Strong experience with Terraform or CloudFormation.

Good-to-Have / Preferred

• Experience working in cybersecurity, fintech, or highly regulated enterprise software companies.
• Experience setting up infrastructure specialized for
• AI/ML workloads
• (handling GPU nodes, managing pipelines for LLMs, or orchestrating vector database deployments).
• Certified Kubernetes Administrator (CKA) or AWS Certified DevOps Engineer Professional.