Location : Bangalore.

Work Mode : OnSite.

Position Name : DevOps Engineer.

Experience : 4 to 9 Years.

About Algotale :

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 rapid, 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.

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