Salary
≈ $12k – $31k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Middle · 4+ years exp
First seen by Alion on Sep 30, 2026.
Overview
Company
Impact
Profile match
IntellifyAi is a technology company developing agentic AI, LLM-powered, and generative AI solutions that transform data and conversations into actionable business decisions.
You will own the cloud infrastructure that runs our AI platforms. Clients choose where their data lives, so we deploy across AWS and Azure in the UK, India, and the Middle East. You will keep those environments reliable, secure, cost-efficient, and repeatable, and you will be the go-to person for infrastructure, security, and uptime questions from our engineers and our clients' IT teams.
Responsibilities:
- Design, build, and manage production, staging, and development environments on AWS and Azure.
- Set up region-specific and client-dedicated deployments to meet data residency needs in the UK, EU, India, and UAE.
- Write infrastructure as code (Terraform, Bicep, ARM, or CloudFormation where needed).
- Build CI/CD pipelines (GitHub Actions, GitLab CI, or Azure DevOps) for Node.js, React, and Python services.
- Run containerized workloads on Kubernetes (EKS and AKS) using Docker, Helm, and autoscaling.
- Own monitoring, logging, and alerting (CloudWatch, Azure Monitor, Prometheus, Grafana).
- Keep real-time voice services within strict latency and uptime targets, and support GPU and inference workloads.
- Lead incident response and root-cause analyses, and maintain runbooks.
- Design and test backup, disaster recovery, and business continuity plans.
- Apply security best practices and support ISO 27001, SOC 2, and GDPR compliance.
- Track and optimize cloud spend across both providers.
What success looks like:
- 30 days: you have mapped our AWS and Azure estate, closed urgent security or reliability gaps, and set up baseline monitoring.
- 90 days: core environments are defined in code, deployments run through CI/CD, and a new client environment can be set up from a template.
- 6 months: uptime and latency reporting is in place, disaster recovery has been tested, and cloud costs are tracked and optimized monthly.
Requirements:
- 4+ years in DevOps, cloud, or SRE roles, with production experience on both AWS and Azure.
- Strong hands-on Terraform or equivalent IaC experience.
- Solid production experience with Docker and Kubernetes (EKS and/or AKS).
- CI/CD experience for Node.js and/or Python applications.
- Good Linux administration, networking, and scripting skills (Bash and Python).
- Working knowledge of cloud security, IAM, and secrets management.
- A calm, methodical approach to incidents and clear communication with engineers and clients.
- Bachelor's degree in computer science, IT, or a related field, or equivalent experience.
Good to have:
- AWS certification (Solutions Architect, DevOps Engineer, or SysOps) and/or Azure certification (AZ-104, AZ-400, or AZ-305).
- Experience deploying AI/ML or LLM inference workloads, including GPU instances.
- Experience with WebRTC, SIP, or TURN/STUN infrastructure.
- Exposure to MongoDB Atlas, Redis, and queues such as Kafka, RabbitMQ, or SQS.
- Experience supporting ISO 27001 or SOC 2 audits.
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