DevOps & AI Infrastructure Engineer

Role Overview

We are looking for a DevOps / Platform Engineer with 3–4 years of experience to help manage AWS cloud infrastructure, automation, and AI-ready platform operations. You will work closely with engineering and AI teams to ensure scalable, secure, and reliable deployments.

Key Responsibilities

1. AWS & Infrastructure: Manage core AWS services (EC2, EKS, Lambda, RDS, S3, VPC) using Infrastructure-as-Code (Terraform, CloudFormation, or CDK).
2. AI/ML Workflows: Support infra for AI applications, model serving, vector databases, and GPU-based workloads.
3. CI/CD & Automation: Build and maintain deployment pipelines using GitHub Actions, GitLab CI, or Jenkins.
4. Containers & Kubernetes: Deploy and maintain containerized applications using Docker and Kubernetes (EKS) or ECS.
5. Observability & Incident Support: Maintain dashboards and alerts with CloudWatch, Prometheus, or Grafana, and participate in on-call response.
6. Security & FinOps: Apply AWS security best practices (IAM, encryption, secrets) and assist with cloud cost optimization.

Must-Have Skills & Qualifications

1. 3–4 years of experience in DevOps, SRE, or Cloud Infrastructure Engineering.
2. AWS & Containers: Good working knowledge of core AWS services, Docker, and Kubernetes (EKS).
3. Infrastructure-as-Code: Practical experience with Terraform, CloudFormation, or AWS CDK.
4. Linux & Networking: Solid fundamentals in Linux systems, DNS, routing, and load balancing.
5. Scripting: Hands-on scripting proficiency in Python, Bash, or Go.
6. CI/CD & Observability: Experience building CI/CD pipelines (GitHub Actions, GitLab CI, or Jenkins) and using monitoring tools (CloudWatch, Prometheus, Grafana, or Datadog).

Nice-to-Have Skills

1. Basic exposure to AI/ML infrastructure, model serving, or GPU-based compute.
2. Experience with event-driven messaging systems (Kafka, Redis, or SQS).
3. Familiarity with GitOps tools and Helm (ArgoCD, Flux, or OpenTelemetry).
4. AWS Certifications (Solutions Architect Associate, SysOps Administrator, or DevOps Engineer).

 The Role 

As a **DevOps Engineer** you'll own the infrastructure and delivery backbone that 

keeps our platform running as we grow. You'll build the CI/CD, cloud infrastructure, and 

observability that let a small, fast-moving team ship confidently — and you'll keep our AI and 

data workloads reliable and affordable at scale. 

This is a hands-on role with real ownership: you won't be maintaining someone else's setup, 

you'll be shaping ours. You'll work closely with the backend, AI/ML, and data teams to make 

deployment boring, incidents rare, and scaling a non-event. --- 

What You'll Own 

**CI/CD & developer experience** 

- Build and maintain fast, reliable CI/CD pipelines so engineers ship multiple times a day with 

confidence. - Make the path from commit to production simple, safe, and repeatable, with sensible 

automated testing, rollbacks, and release controls. 

**Cloud infrastructure & IaC** - Own our cloud infrastructure (AWS/GCP) end to end, managed as code (Terraform or 

similar) — no click-ops. - Design for scale and cost-efficiency as store and conversation volumes grow. 

**Containers & orchestration** - Run our services on containers/Kubernetes: deployments, autoscaling, networking, and 

resource management. - Support the specific needs of AI/ML workloads, including GPU-backed inference and batch 

processing for the speech pipeline. 

**Reliability & observability (SRE)** - Own uptime, performance, and incident response — monitoring, logging, tracing, alerting, 

on-call, and blameless postmortems. - Define and defend SLOs; keep the platform dependable as it scales across clients. 

**Data & pipeline infrastructure** - Support the infrastructure behind large-scale, edge-to-cloud data movement and 

processing (audio ingestion, ASR/AI pipelines, analytics). - Keep data workloads reliable, performant, and cost-aware. 

**Security & compliance** - Bake security into the platform: secrets management, IAM/least-privilege, encryption in 

transit and at rest, network hardening, and vulnerability management. - Support compliance readiness (including India's DPDP Act and enterprise-client security 

requirements) for a product that handles sensitive customer conversations. 

**Cost & scale** - Own cloud cost visibility and optimization; make scaling decisions that balance reliability 

and spend. --- 

What You'll Bring - 6+ years in DevOps, SRE, platform, or infrastructure engineering, running production 

systems at meaningful scale. - Strong hands-on experience with a major cloud provider (**AWS or Azure or GCP**) and 

Infrastructure-as-Code (**Terraform** or equivalent). - Solid experience with **containers and Kubernetes** in production. - Experience building and owning **CI/CD** pipelines (e.g. GitHub Actions, GitLab CI, 

Jenkins, Argo, or similar). 

- Comfort with a scripting/automation language (Python, Go, or Bash) and a strong 

automation-first mindset. - Real experience with **observability** (Prometheus/Grafana, ELK, Datadog, 

OpenTelemetry, or similar) and running incident response / on-call. - A security-conscious approach — secrets, IAM, encryption, and least-privilege as defaults. - Startup temperament: ownership, pragmatism, and a bias to automate and ship. - Based in or willing to relocate to Bangalore, and up for an onsite/hybrid, in-person team. 

Bonus Points - Experience running **ML/AI or GPU workloads** in production (inference serving, batch 

pipelines, model deployment). - Experience with data-intensive infrastructure — streaming/queues (Kafka, SQS), data 

pipelines, or large object/audio storage. - Exposure to **edge devices / IoT fleets**, OTA updates, or high-volume device-to-cloud 

ingestion. - Experience with compliance/security frameworks (SOC 2, ISO 27001, DPDP). - FinOps / cloud cost-optimization experience. - Early-stage startup experience. --- 

Why Join - Own infrastructure that's already live with leading retail brands and growing fast — real 

scale, real impact. - Work across genuinely interesting workloads: speech AI, GPU inference, large-scale data, 

and edge-to-cloud ingestion. - Small team, high ownership, direct line to engineering leadership — your decisions ship. - Build the platform foundation of a category-defining product from an

Job Title : Senior AWS DevSecOps & AI Platform Engineer

Experience Required : 5+ Years in AWS / Cloud Engineering

Terraform Experience : 4+ Years

Location : Gurugram

Work Mode : Onsite

Employment Type : Full-time

About the Role :

We are looking for an experienced Senior AWS DevSecOps & AI Platform Engineer with strong expertise in AWS cloud infrastructure, Kubernetes, Infrastructure as Code (IaC), CI/CD automation, cloud security, and database administration.

The ideal candidate will be responsible for designing and maintaining secure, scalable, reliable, and cost-efficient cloud environments while supporting microservices-based applications and implementing DevSecOps best practices. The role also involves building and deploying AI agents using Amazon Bedrock and Bedrock AgentCore, along with managing enterprise development and collaboration tools.

Mandatory Skills :

AWS (EC2, EKS, ECS, Lambda, S3, CloudWatch), Kubernetes, Terraform, Jenkins, Bitbucket Pipelines, CI/CD, DevSecOps, AWS Security Services (IAM, WAF, GuardDuty, Security Hub, KMS, Secrets Manager), Microservices, Helm, PostgreSQL, Oracle SQL, RDS, Jira, Confluence, Amazon Bedrock, Bedrock AgentCore, AWS Networking, and Cloud Cost Optimization.

Key Responsibilities :

• AWS Cloud Infrastructure : Design, implement, and maintain AWS infrastructure with a focus on scalability, availability, security, reliability, and cost optimization.
• Microservices & Containerization : Manage and support distributed microservices architectures, including deployment, monitoring, troubleshooting, performance optimization, service meshes, and API gateways.
• Kubernetes Administration : Administer and optimize Kubernetes clusters, including Amazon EKS and self-managed environments, covering upgrades, networking, workload management, scaling, and resource optimization.
• Cloud Security & Compliance : Implement and manage AWS security services, including IAM, GuardDuty, Security Hub, WAF, KMS, Secrets Manager, AWS Config, and CloudTrail.
• DevSecOps Implementation : Integrate security testing, vulnerability scanning, container security, and compliance-as-code tools into CI/CD pipelines.
• CI/CD & Source Control : Manage Bitbucket repositories, branching strategies, permissions, and Bitbucket Pipelines. Build and optimize Jenkins pipelines using declarative and scripted approaches.
• Infrastructure as Code : Develop and maintain Terraform modules, manage remote state and workspaces, detect infrastructure drift, and implement reusable infrastructure provisioning practices.
• Database Administration : Provision, manage, secure, and optimize AWS RDS databases, particularly PostgreSQL and Oracle, including backups, replication, patching, performance tuning, and migrations.
• Jira & Confluence Administration : Manage projects, workflows, automation rules, permissions, user access, spaces, schemes, and plugins.
• Monitoring & Reliability : Define and monitor SLIs, SLOs, and SLAs; implement observability best practices; and participate in incident management, root cause analysis, and post-incident reviews.
• AI Agent Development : Design, build, and deploy AI agents using Amazon Bedrock and Bedrock AgentCore, including agent runtime, memory, tools, gateway integration, identity and access management, guardrails, and lifecycle management across environments.
• Cloud Connectivity : Support hybrid cloud connectivity using AWS Direct Connect, VPN, and Transit Gateway.
• Cost Optimization : Apply FinOps practices to monitor cloud expenditure, optimize resource utilization, and improve infrastructure efficiency.
• API Integrations : Integrate third-party APIs while implementing authentication, rate limiting, error handling, and webhook management.

Required Skills & Qualifications :

• 5+ years of hands-on experience with AWS cloud services, including EC2, ECS, EKS, Lambda, ALB, CDN, S3, CloudWatch, Amazon Bedrock, and Bedrock AgentCore.
• Strong understanding of AWS networking, multi-account strategies, landing zone architecture, and hybrid connectivity.
• 4+ years of practical experience with Terraform, including module development, remote state management, workspaces, drift detection, and state operations.
• Extensive experience administering Kubernetes, preferably Amazon EKS, including Helm, Kustomize, operators, RBAC, network policies, autoscaling, and multi-tenancy.
• Proven experience managing distributed microservices, service meshes, API gateways, and inter-service communication.
• Strong knowledge of AWS security services, including IAM, Service Control Policies (SCPs), WAF, KMS, Secrets Manager, AWS Config, and CloudTrail.
• Experience implementing least-privilege access, zero-trust principles, and cloud security compliance controls.
• Hands-on experience integrating DevSecOps tools such as Snyk, Trivy, Checkov, and SonarQube into CI/CD pipelines.
• Understanding of OWASP security principles, CIS benchmarks, vulnerability management, and container security.
• Proficiency in Bitbucket repository administration, branch permissions, and YAML-based Bitbucket Pipelines.
• Strong experience developing and maintaining Jenkins CI/CD pipelines, shared libraries, plugins, and build agents.
• Experience administering AWS RDS databases, particularly PostgreSQL and Oracle SQL, including backup, replication, performance tuning, and migration activities.
• Experience administering Jira and Confluence, including workflows, permissions, automation, and plugin management.
• Working knowledge of Azure services, particularly Web Apps and Logic Apps/Workflows.
• Practical experience with Amazon Bedrock, including model invocation, guardrails, and AI agent development and deployment using Bedrock AgentCore.
• Understanding of third-party API integration, authentication mechanisms, rate limiting, error handling, and webhook management.
• Familiarity with FinOps practices and cloud cost optimization.

Good-to-Have Skills :

• Additional Azure experience, including networking, Azure SQL Managed Instance, and Azure Kubernetes Service (AKS).
• Hands-on experience with AI-driven Development Lifecycle (AI-DLC) methodologies and tools such as Kiro.

Relevant certifications, such as :

• AWS Certified Solutions Architect
• AWS Certified DevOps Engineer – Professional
• AWS Machine Learning or Generative AI certifications
• Certified Kubernetes Administrator (CKA)
• HashiCorp Terraform certifications

Ideal Candidate Profile :

The ideal candidate is a hands-on cloud and DevSecOps professional who can manage enterprise-scale AWS infrastructure, automate deployments, strengthen security controls, troubleshoot complex distributed systems, and support AI agent development. Strong problem-solving skills, an automation-first mindset, and the ability to collaborate across development, security, and infrastructure teams are essential.

Company Overview:

Planview is hiring a DevOps Engineer in Bengaluru, India to support Planview SaaS applications across the product line. You will work in a global, collaborative team — owning CI/CD pipelines, cloud infrastructure, and automation to keep deployments fast and systems reliable.

Responsibilities

• Build and maintain CI/CD pipelines in Jenkins for reliable, fast delivery.
• Manage containerized workloads on Docker and ECS — task definitions, services, and clusters.
• Provision and manage AWS infrastructure using Terraform (CloudFormation a plus).
• Automate configuration and deployment tasks using Python (Ansible a plus).
• Set up and maintain monitoring and alerting via New Relic (CloudWatch, Datadog, or Prometheus/Grafana a plus).
• Write Shell and Python scripts to automate operations and reduce manual work.
• Manage Git workflows — branching, merge strategies, and pull request reviews.
• Administer and support MSSQL databases underpinning the product line — backups, restores, and basic performance troubleshooting.
• Troubleshoot deployment, performance, and infrastructure issues with development teams.
• Participate in on-call rotations and drive incident response.
• Continuously improve infrastructure resilience and deployment speed.
• Apply AI-assisted engineering tools (e.g., GitHub Copilot, Claude Code) to speed up IaC authoring, pipeline debugging, and day-to-day scripting.

Qualifications

Must-Have Skills

• Experience: 4–6 years of experience in DevOps, SRE, or Infrastructure Engineering.
• OS: Windows administration (systemd, package management, log analysis).
• Cloud: AWS (Active Directory, ECS, EC2, CloudFront, S3, VPC, IAM, RDS, Lambda basics).
• Source Control: Git — branching, merge/rebase, PR reviews.
• CI/CD (Jenkins): Pipeline creation and basic Groovy scripting.
• Containerization (Docker + ECS): Task definitions, services, and clusters.
• IaC: Terraform.
• Monitoring: New Relic.
• Scripting: Bash and Python scripting for automation.
• Networking Basics: DNS, load balancers, security groups, VPNs.
• Logging: ELK stack / CloudWatch Logs.
• Database: MSSQL administration — backups, restores, basic performance troubleshooting.
• Infrastructure Automation: Hands-on experience automating infrastructure provisioning, configuration, and deployment end-to-end.
• AI-Assisted Engineering: Comfortable working with AI coding/DevOps assistants (e.g., GitHub Copilot, Claude Code) for IaC generation, scripting, and troubleshooting — verified via a mandatory AI proficiency assessment during interviews.

Nice-to-Have Skills

•     Configuration Management: Ansible.

•     Additional IaC: CloudFormation.

•     Architecture: Knowledge of microservices architecture.

•     Cloudflare: DNS, CDN, WAF.

•     Artifact Repositories: Nexus, JFrog Artifactory, ECR.

•     Other CI/CD Tools: GitHub Actions.

•     AWS cost optimization / FinOps awareness.

•     Datadog, CloudWatch, or Prometheus/Grafana.

•     AIOps: Exposure to AI-driven anomaly detection, root-cause analysis, or incident triage (e.g., Dynatrace Davis AI, Datadog Bits AI, Harness AIDA).

•     Database Basics: RDS backups, restores, performance tuning.

Key Responsibilities

• Automate application deployments from Bitbucket to servers using CI/CD pipelines.
• Design and manage scalable, highly available AWS infrastructure.
• Implement Auto Scaling, ELB, and Route 53 for traffic management and high availability.
• Work with AWS services including IAM, RDS, DynamoDB, EC2, and other cloud services.
• Build and manage Docker containers and server images.
• Deploy and manage applications using Kubernetes.
• Implement Infrastructure as Code using Terraform, CloudFormation, or Ansible.
• Develop automation scripts using Python and Bash.
• Implement monitoring and logging using tools such as Prometheus, Grafana, and ELK.
• Integrate security and compliance practices into CI/CD pipelines.
• Optimize infrastructure for security, scalability, performance, and cost.

Required Skills

• 3+ years of experience in DevOps or a similar role.
• Strong knowledge of AWS beyond EC2.
• Hands-on experience with Jenkins or similar CI/CD tools.
• Experience with Docker and Kubernetes.
• Good understanding of Terraform/IaC and automation.
• Proficiency in Python and/or Bash scripting.
• Knowledge of DevSecOps, security, and compliance best practices.
• Strong troubleshooting and problem-solving skills.

About the Role

We are looking for an experienced AWS DevOps Engineer with around 4 years of hands-on experience to join our infrastructure/DevOps team. The ideal candidate will independently design, deploy, and maintain cloud infrastructure primarily on AWS, drive automation initiatives, mentor junior engineers, and work closely with cross-functional teams to build scalable, secure, and highly available systems. Exposure to Azure is a strong plus.

Key Responsibilities

·      Design, deploy, and maintain robust, scalable, and secure infrastructure on AWS

·      Architect and manage core AWS services such as EC2, S3, VPC, IAM, RDS, Lambda, ECS/EKS, Route 53, and CloudFront

·      Build, own, and optimize CI/CD pipelines (e.g., CodePipeline, Jenkins, GitLab CI, GitHub Actions) to enable fast and reliable deployments

·      Design and implement Infrastructure as Code (IaC) using Terraform / AWS CloudFormation

·      Set up and manage monitoring, logging, and alerting solutions (CloudWatch, ELK, Prometheus, Grafana, Datadog, etc.)

·      Implement and enforce security best practices including IAM policies, security groups, NACLs, KMS, Secrets Manager, and compliance standards

·      Lead troubleshooting and root cause analysis for infrastructure, deployment, and production incidents

·      Drive backup, disaster recovery, high-availability, and cost-optimization strategies (Reserved Instances, Savings Plans, right-sizing)

·      Containerize applications and manage orchestration using Docker, ECS, and/or Kubernetes (EKS)

·      Automate repetitive operational tasks through scripting and tooling

·      Support any hybrid or multi-cloud initiatives involving Azure services, where applicable

·      Mentor junior engineers and review their work, providing technical guidance

·      Collaborate with development, QA, security, and product teams to support and streamline application deployments

·      Maintain comprehensive documentation of architecture, configurations, processes, and runbooks

·      Participate in on-call rotations and incident response as needed

Required Skills & Qualifications

·      Bachelor's degree in Computer Science, IT, or a related field (or equivalent practical experience)

·      4+ years of hands-on experience working with AWS cloud services in a production environment

·      Strong expertise in core AWS services: EC2, S3, VPC, IAM, RDS, Lambda, CloudWatch, ECS/EKS, Route 53, ELB/ALB, Auto Scaling

·      Solid understanding of networking concepts (subnets, routing, security groups, load balancers, VPNs, VPC peering, Direct Connect)

·      Strong scripting/programming skills in Python, Bash, or PowerShell for automation

·      Hands-on experience with Infrastructure as Code tools such as Terraform or AWS CloudFormation

·      Proven experience with Linux and/or Windows server administration

·      Strong understanding of CI/CD pipelines, Git-based version control, and branching strategies

·      Solid experience with containerization and orchestration (Docker, ECS, or EKS/Kubernetes)

·      Experience with configuration management tools (Ansible, Chef, or Puppet) is a plus

·      Application Server Management — strong knowledge of networking, firewalls, load balancers, Nginx, Apache, etc.

·      Ability to independently read, interpret AWS documentation, and troubleshoot complex issues

·      Experience with cost optimization, security audits, and compliance frameworks (e.g., ISO, SOC2) is a plus

·      AWS certification (Solutions Architect Associate/Professional, DevOps Engineer Professional) preferred

Good to Have

·      Working knowledge of Microsoft Azure services (Virtual Machines, VNets, Azure DevOps, Azure Storage, Azure AD/Entra ID, AKS)

·      Experience with multi-cloud or hybrid-cloud environments

·      Familiarity with Azure Resource Manager (ARM) templates or Bicep

·      Any Azure certification (AZ-104, AZ-400, etc.)

Soft Skills

·      Strong analytical, problem-solving, and decision-making ability

·      Excellent verbal and written communication skills

·      Ability to mentor and guide junior team members

·      Proactive, ownership-driven approach to infrastructure and incident management

·      Strong collaboration skills in a cross-functional, team-oriented environment

·      High attention to detail with a focus on reliability and scalability

About the company:

We empower US healthcare payers with a truly next-generation, cloud-native, holistic, and customizable platform designed to prevent and adapt to the ever-evolving inaccuracies in healthcare claims and payments. By reducing complexity and administrative costs, we offer a unified, healthcare-dedicated platform backed by top VCs like BeeNext, 3One4 Capital, and Saison Capital.

Position Overview:

We are looking for an experienced DevOps Engineer to join our team in Bengaluru. In this role, you will be responsible for building, optimizing, and maintaining scalable, secure, and highly available multi-cloud infrastructure that supports our engineering teams. The ideal candidate brings strong hands-on experience with Kubernetes, Infrastructure as Code (Terraform), and robust monitoring/observability stacks to enable seamless, reliable, and automated deployments.

Key Responsibilities:

• Container Orchestration: Deploy, scale, and manage containerized workloads on Kubernetes (EKS, AKS, and GKE).
• Infrastructure as Code (IaC): Build and maintain modular, reusable, and version-controlled infrastructure using Terraform across AWS, Azure, and GCP.
• Monitoring & Observability: Set up, manage, and optimize monitoring, logging, and alerting stacks (e.g., Prometheus, Grafana, ELK/EFK, Loki, Datadog).
• CI/CD Pipeline Management: Own, improve, and automate CI/CD pipelines to enable fast, reliable, and frictionless software releases.
• System Reliability & SRE Practices: Implement best practices for system reliability, including defining SLIs/SLOs, managing incident response, and participating in on-call support.
• Troubleshooting & Support: Diagnose and resolve complex production issues across infrastructure, networking, and application layers.
• Security & Compliance: Implement infrastructure security best practices, including IAM policies, secrets management, and network security.
• Automation: Eliminate repetitive operational tasks by writing clean, efficient scripts in Python, Bash, or Go.
• Operations & Planning: Participate in capacity planning, cost optimization, disaster recovery, and infrastructure scaling initiatives while maintaining clear documentation and runbooks.

Requirements :

• Solid working experience with cloud providers, specifically AWS, Azure, or GCP.
• Strong understanding of containerization (Docker) and container orchestration concepts.
• Familiarity with Linux system administration and networking fundamentals.
• Experience with version control systems (Git) and GitOps workflows (ArgoCD/Flux is a plus).
• Strong problem-solving skills and the ability to thrive in a fast-paced, collaborative environment.

Qualifications :

Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related technical field (or equivalent practical experience)

Key Skills:

• The ideal candidate must possess deep expertise in container orchestration, specifically hands-on experience managing Kubernetes ecosystems—including Helm charts, cluster networking, and RBAC policies—alongside a foundational mastery of Docker containerization.
• Proficiency in managing cloud architecture as software is essential, with a heavy emphasis on Terraform execution, including advanced module creation, state management, and multi-environment workspaces.
• A strong capability to implement full-stack visibility is required, utilizing tools like Prometheus, the Grafana LGMT stack, ELK/EFK, or Loki to build highly optimized monitoring, alerting, and logging systems.
• Candidates should have a proven track record of constructing and scaling automated deployment pipelines using industry-standard platforms such as Jenkins, GitLab CI, GitHub Actions, or Azure DevOps to minimize release friction. .
• Strong core programming fundamentals are required to automate repetitive infrastructure tasks, with practical proficiency in Python, Bash, or Go.
• Familiarity with cutting-edge cloud-native technologies is highly desirable, including enterprise service meshes (Istio, Linkerd), comprehensive cloud security frameworks (HashiCorp Vault, OPA, Trivy), and a data-driven approach to cloud cost management and FinOps practices.

Work Location: Jayanagar - Bangalore.

Work Mode: Work from Office, hybrid- 3 days WFO

Note: We are looking for immediate joiners & Bangalore Candidates only

Benefits:

• Best-in-class compensation
• Health insurance for Family
• Personal Accident Insurance
• Friendly and Flexible Leave Policy
• Certification and Course Reimbursement
• Medical Coding CEUs and Membership Renewals
• Health checkup
• And many more!

Job Title: Java AWS Kubernetes DevOps AI/ML

Experience: 8–10 Years

The candidate should have at least 1 year of experience in AI/ML and hands-on experience with the below technologies:

Java

AWS

Kubernetes

DevOps

AI/ML

MongoDB / PostgreSQL

Key-Value Caching

Vector Databases – ChromaDB / Pgvector

Job Specification:

Work Experience: 7 to 10 Years

Work Location:  Bangalore

Mode of Employment: Permanent

Education Qualification required: Any Degree

Job Description:

We are looking for an experienced DevOps Engineer with strong expertise in Linux, CI/CD, containerization, cloud platforms, Infrastructure as Code (IaC), and observability. The ideal candidate should have hands-on experience with Kubernetes, OpenShift, Terraform, scripting, DevSecOps, and modern monitoring practices.

Responsibilities:

• Manage and maintain Linux-based systems, cloud infrastructure, and production environments.
• Develop, maintain, and optimize CI/CD pipelines using Git and related automation tools.
• Deploy and manage containerized applications using Docker, Kubernetes (K8s), and OpenShift.
• Provision and manage cloud infrastructure on AWS and/or Microsoft Azure.
• Automate infrastructure provisioning and configuration using Terraform.
• Develop automation scripts using Python and Shell scripting.
• Implement observability and monitoring solutions using Prometheus, Grafana, AppDynamics, and Splunk.
• Troubleshoot production incidents, perform root cause analysis (RCA), and improve system reliability and availability.
• Implement DevSecOps practices, security controls, and vulnerability management across CI/CD pipelines.
• Manage cloud networking, connectivity, and infrastructure-related configurations.
• Support AIOps initiatives to improve incident detection, analysis, and operational efficiency.
• Manage SSL/TLS certificates, secrets, and secure credential rotation.

Required Skills:

• Strong hands-on experience with Linux.
• Good knowledge of Git and CI/CD pipelines.
• Experience with Docker, Kubernetes (K8s), and/or OpenShift.
• Working experience with AWS and/or Microsoft Azure.
• Hands-on experience with Terraform and Infrastructure as Code (IaC).
• Scripting knowledge in Python and/or Shell.
• Experience with Prometheus, Grafana, AppDynamics, and/or Splunk.
• Knowledge of DevSecOps, networking, and cloud security fundamentals.
• Understanding of AIOps concepts and automated operations.
• Experience with certificate lifecycle management and secrets management.

TECHJAYS

THE AI REIMAGINATION COMPANY

Position DevOps Lead

Experience 10+ Years

Location Coimbatore / Hybrid

Joining Immediate / ASAP

Primary SkillsDevOps, AWS or Azure, CI/CD, Kubernetes, Docker, Terraform, Linux, Git, Cloud Infrastructure, Infrastructure Automation, Monitoring & Observability

Preferred SkillsAI/ML Infrastructure Exposure, GenAI Applications, GitOps, Argo CD, Prometheus, Grafana, Python, Bash, PowerShell, Cloud Security, FinOps

About Techjays

At Techjays, we're helping businesses reimagine how they build, operate, and scale with AI at the core. We focus on developing secure, scalable, production-grade AI systems that solve complex business challenges and deliver measurable business outcomes.

Our team brings together experienced engineers and technology leaders from organizations such as Google, NetApp, ADP, Cognizant Consulting, and Capgemini. We work with global clients to build advanced AI-powered applications, enterprise platforms, and intelligent automation solutions.

We're looking for a DevOps Lead who can take ownership of cloud infrastructure, deployment automation, CI/CD pipelines, platform reliability, and engineering operations.

The ideal candidate will have deep hands-on expertise in either AWS or Azure, along with strong experience in Kubernetes, containerization, Infrastructure as Code, and production cloud environments.

You will lead the design and implementation of reliable infrastructure platforms, establish DevOps best practices, and work closely with software engineering and AI teams to support the deployment and operation of modern applications.

This role requires a strong hands-on cloud and DevOps specialist who can architect, implement, troubleshoot, and optimize production infrastructure. Prior exposure to AI/ML or AI-enabled applications is required, but specialized MLOps expertise is not mandatory.

Key Responsibilities

1. Cloud Infrastructure & Architecture

• Lead the design, implementation, and management of scalable, secure, and highly available cloud infrastructure.
• Own cloud infrastructure architecture and operations across AWS or Azure.
• Design and manage cloud environments covering compute, networking, storage, databases, and container platforms.
• Establish infrastructure standards, architecture patterns, and operational best practices.
• Manage cloud resource provisioning, configuration, scaling, and environment management.
• Ensure infrastructure meets requirements for availability, performance, security, and reliability.
• Drive infrastructure improvements through automation and continuous optimization.

2. DevOps & CI/CD Engineering

• Design, implement, and maintain CI/CD pipelines for application development and deployment.
• Manage multi-stage deployment workflows across development, testing, staging, and production environments.
• Implement automated build, testing, deployment, and release processes.
• Establish reusable pipeline templates, deployment standards, and approval workflows.
• Manage deployment strategies, including rolling, blue/green, and canary deployments.
• Implement rollback mechanisms and ensure reliable production releases.
• Integrate CI/CD workflows with source control, artifact repositories, and container registries.
• Continuously improve deployment efficiency, release reliability, and engineering productivity.

3. Containerization & Kubernetes Management

• Architect and manage containerized application environments using Docker and Kubernetes.
• Manage production Kubernetes clusters using Amazon EKS or Azure AKS.
• Implement Kubernetes configurations covering deployments, services, networking, secrets, storage, and resource management.
• Work with Helm charts for application packaging and deployment.
• Optimize container resource utilization, application scaling, and cluster performance.
• Troubleshoot complex container and Kubernetes-related production issues.
• Establish best practices for container security and workload reliability.

4. Infrastructure as Code & Automation

• Implement Infrastructure as Code using Terraform and cloud-native provisioning tools.
• Automate infrastructure provisioning, configuration management, and environment setup.
• Develop reusable infrastructure modules and deployment automation workflows.
• Use Python, Bash, or PowerShell to automate operational tasks and improve efficiency.
• Reduce manual intervention through standardization and automation.
• Maintain infrastructure documentation, configuration standards, and version-controlled deployment workflows.

5. Monitoring, Reliability & Production Operations

• Establish centralized monitoring, logging, alerting, and observability across cloud environments.
• Implement monitoring solutions using CloudWatch, Azure Monitor, Prometheus, Grafana, or equivalent platforms.
• Monitor application availability, infrastructure health, resource utilization, and system performance.
• Lead troubleshooting and resolution of complex production incidents.
• Conduct root cause analysis and implement permanent corrective actions.
• Establish operational practices for backup, disaster recovery, availability, and business continuity.
• Improve system reliability through proactive monitoring and performance optimization.

6. Cloud Security & Governance

• Implement cloud security best practices across infrastructure and application environments.
• Manage IAM, RBAC, access controls, service identities, and secrets management.
• Secure cloud networking, virtual networks, firewalls, and infrastructure access.
• Implement container security and infrastructure hardening practices.
• Ensure cloud environments follow organizational security and compliance requirements.
• Identify infrastructure vulnerabilities and coordinate remediation activities.
• Establish secure deployment and configuration management practices.

7. AI Infrastructure & Engineering Collaboration

• Work closely with AI/ML and software engineering teams to provide infrastructure for AI-powered applications.
• Support the deployment and operation of LLM-based applications, AI services, and AI-enabled platforms.
• Design cloud infrastructure capable of supporting AI workloads, including compute, storage, networking, and containerized services.
• Support the infrastructure requirements of AI applications across development, testing, and production environments.
• Collaborate with engineering teams to improve deployment reliability, scalability, and operational performance of AI-powered systems.
• Evaluate infrastructure technologies and tools that support evolving AI application requirements.

8. Technical Leadership & Team Development

• Provide technical leadership to DevOps engineers and guide implementation across projects.
• Establish engineering standards, infrastructure best practices, and operational procedures.
• Mentor team members on cloud architecture, automation, CI/CD, Kubernetes, and production operations.
• Lead technical discussions and make architecture decisions involving infrastructure and DevOps technologies.
• Collaborate with engineering, security, and product teams to align infrastructure capabilities with business requirements.
• Drive continuous improvement across DevOps processes, tools, and engineering practices.

Required Technical Skills & Experience

1. Cloud Platforms

• 10+ years of overall experience in DevOps, cloud infrastructure, or platform engineering.
• Strong hands-on expertise in at least one major cloud platform: AWS or Azure.
• Practical experience designing, deploying, and operating production-grade cloud infrastructure.

AWS: EC2, S3, IAM, VPC, EKS, Lambda, ECR, CloudWatch, and related infrastructure services.

Azure: Azure Virtual Machines, VNets, AKS, Azure DevOps, Azure Container Registry, Azure Monitor, Key Vault, and related infrastructure services.

Candidates do not need to be experts in both AWS and Azure. Deep expertise in either platform is the priority.

2. DevOps & CI/CD

• Strong experience designing and maintaining CI/CD pipelines.
• Hands-on experience with Azure DevOps, Jenkins, GitHub Actions, GitLab CI, or equivalent tools.
• Understanding of multi-stage pipelines, automated deployments, release approvals, and artifact management.
• Experience implementing deployment automation and rollback strategies.
• Strong understanding of Git workflows and version control practices.

3. Containers & Kubernetes

• Strong hands-on experience with Docker and Kubernetes.
• Practical experience managing EKS or AKS environments.
• Understanding of Kubernetes networking, scaling, storage, secrets, and workload management.
• Experience with Helm and container orchestration.
• Ability to troubleshoot production container and Kubernetes environments.

4. Infrastructure as Code & Scripting

• Strong experience with Terraform and Infrastructure as Code practices.
• Familiarity with CloudFormation, Bicep, ARM templates, or similar tools.
• Working knowledge of Python, Bash, or PowerShell for infrastructure automation.
• Strong understanding of Linux administration and system troubleshooting.

5. Monitoring & Reliability Engineering

• Experience implementing infrastructure and application monitoring.
• Familiarity with CloudWatch, Azure Monitor, Prometheus, Grafana, and centralized logging solutions.
• Understanding of incident management, root cause analysis, performance optimization, and system availability.
• Experience establishing alerting, operational dashboards, and reliability practices.

6. AI/ML Infrastructure Exposure

• Prior experience supporting AI/ML applications, Generative AI platforms, LLM applications, or AI-enabled products.
• Understanding of infrastructure requirements for deploying and operating AI-powered applications.
• Familiarity with containerized AI services, cloud-based model integrations, and scalable application environments.

Note: This role does not require specialized MLOps expertise or model development experience. Strong cloud and DevOps engineering fundamentals remain the primary requirement.

Preferred Skills

• Experience implementing GitOps workflows using Argo CD or similar tools.
• Experience with blue/green deployments, canary releases, and automated rollback mechanisms.
• Exposure to cloud security, enterprise networking, governance, and landing-zone architecture.
• Experience with cloud cost optimization and FinOps practices.
• Familiarity with AI/ML infrastructure and production GenAI applications.
• Experience with Python-based automation and infrastructure tooling.
• Relevant AWS, Azure, Kubernetes, or Terraform certifications.

What We're Looking For Beyond Skills

• Cloud Expertise: Deep technical specialization in AWS or Azure, with the ability to design and manage production infrastructure independently.
• Hands-on Engineering: Someone who actively builds, automates, troubleshoots, and improves infrastructure rather than focusing only on team management.
• Technical Ownership: Takes responsibility for infrastructure reliability, deployment quality, security, and operational performance.
• System Thinking: Understands how cloud infrastructure, applications, networking, databases, and deployment pipelines work together.
• Problem-Solving: Ability to diagnose complex production issues and implement long-term engineering solutions.
• Automation Mindset: Continuously identifies opportunities to eliminate manual work and improve operational efficiency.
• Technical Leadership: Can mentor engineers, establish best practices, and drive technical decisions.
• AI Readiness: Has practical exposure to supporting AI-powered applications and understands their infrastructure requirements.
• Collaboration: Works effectively with software engineering, AI/ML, security, and product teams.

Typical Technology Environment

AreaTechnologiesCloud PlatformsAWS, AzureCI/CDAzure DevOps, GitHub Actions, Jenkins, GitLab CIContainersDocker, Kubernetes, EKS, AKS, HelmInfrastructure as CodeTerraform, CloudFormation, Bicep, ARMGitOpsArgo CD, Git-based deployment workflowsMonitoring & ObservabilityCloudWatch, Azure Monitor, Prometheus, GrafanaAutomationPython, Bash, PowerShellOperating SystemsLinux, WindowsSecurityIAM, RBAC, Secrets Management, Network SecurityAI ExposureAI/ML Applications, GenAI, LLM Platforms, AI-enabled Products

What We Offer

• Competitive compensation aligned with experience and expertise.
• Coimbatore office-based work environment with hybrid flexibility.
• Opportunity to lead cloud infrastructure and DevOps engineering for global clients.
• Exposure to modern AWS/Azure, Kubernetes, automation, and AI engineering practices.
• Paid holidays and flexible time off.
• Medical insurance covering self and family, up to ₹4 lakh per person.
• Opportunities to influence infrastructure architecture and engineering practices.
• A culture that values clarity, integrity, ownership, and continuous growth.

Join Techjays

If you're passionate about building reliable cloud platforms, automating complex infrastructure, and leading DevOps engineering for modern AI-powered applications, we'd love to hear from you.