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Salary
≈ $23k – $51k per year (Estimated)
Location
In office (Coimbatore)
Seniority
Staff · 5+ years exp

First seen by Alion on Oct 7, 2026.

Overview
Company
Impact
Profile match
Management Consultants, Placement and Recruitment Consultants, HR Consultants, Symbiosis Management Consultants.

Role Summary :

The Lead Engineer - CloudOps, DevSecOps & AI Platform Engineering will be responsible for end-to-end delivery ownership of cloud platforms, AI platforms, DevSecOps pipelines, and operational excellence for one or more programs or domains.

This role combines technical leadership, architecture ownership, delivery governance, AI platform management, MCP integration, and cross-team coordination, while remaining hands-on for critical systems, cloud infrastructure, Kubernetes platforms, and AI-enabled engineering solutions.

Key Responsibilities :

Cloud Platform Ownership :

- Own architecture, design, and operational stability of AWS and GCP cloud environments (Pre-Prod and Prod).

- Design and maintain enterprise-grade landing zones including multi-VPC networking, IAM guardrails, logging, and security baselines.

- Define and enforce high availability, scalability, and resilience strategy for cloud workloads.

- Lead DR and backup strategy implementation with validated RTO/RPO compliance through testing and drills.

DevSecOps & CI/CD Leadership :

- Own the design and continuous improvement of CI/CD pipelines for microservices, IoT workloads, serverless, and mobile-backend platforms.

- Define DevSecOps standards embedding security at every stage including SAST and SCA.

Kubernetes & Platform Engineering :

- Lead Kubernetes platform engineering and container orchestration.

Reliability Engineering & Incident Management :

- Own SLAs, SLOs, and operational KPIs for hosting platforms.

- Lead major incident response, root-cause analysis, and preventive remediation.

- Implement proactive reliability and performance improvement initiatives.

Operational Excellence & Optimization :

- Monitor and improve key DevOps and SRE metrics : deployment frequency, failure rate, MTTR, lead time to recovery.

Technical Skills :

- Cloud : AWS and/or GCP (advanced, hands-on)

- DevSecOps : Jenkins, GitHub/Gerrit, SonarQube/SAST, Vault, Trivy/Clair, OWASP

- IaC : Terraform (expert), Helm, Ansible

- Containers : Docker, Kubernetes (EKS/ECS or GKE)

- Scripting : Shell & Python (mandatory)

- Monitoring : ELK, Grafana, Prometheus, Splunk/Dynatrace

- AI & MCP : Model Context Protocol (MCP), AI Agent Frameworks and AI-driven automation.

- Networking : VPCs, Load Balancers, API Gateway, VPNs, WAF, DNS

Mandatory Requirements :

- AWS or GCP Solution Architect certification (Professional level).

- Certified Kubernetes Administrator (CKA).

- Exposure to MLOps (SageMaker, Bedrock) or Data Platforms (Delta Lake).

Skills

Cloud Services, DevSecOps, Cloud Operations, CI/CD, Kubernetes, Site Reliability, Incident Management, Monitoring Tools, IAC Terraform

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