Site Reliability Engineer at Wissen Technology · Bengaluru (Bangalore) · 4 - 8 years · ₹10L - ₹20L / yr · Profitable · Posted 5 May 2025

- 2+ years of hands-on experience in Java development.
- Strong knowledge of Boto3/Boto AWS libraries (Python).
- Solid experience with AWS services: EC2, ELB/ALB, CloudWatch.
- Familiarity with SRE practices and maintenance processes.
- Strong experience in debugging, troubleshooting, and unit testing.
- Proficiency with Git and CI/CD tools.
- Understanding of distributed systems and cloud-native architecture.

About Wissen Technology
About
The Wissen Group was founded in the year 2000. Wissen Technology, a part of Wissen Group, was established in the year 2015. Wissen Technology is a specialized technology company that delivers high-end consulting for organizations in the Banking & Finance, Telecom, and Healthcare domains.
With offices in US, India, UK, Australia, Mexico, and Canada, we offer an array of services including Application Development, Artificial Intelligence & Machine Learning, Big Data & Analytics, Visualization & Business Intelligence, Robotic Process Automation, Cloud, Mobility, Agile & DevOps, Quality Assurance & Test Automation.
Leveraging our multi-site operations in the USA and India and availability of world-class infrastructure, we offer a combination of on-site, off-site and offshore service models. Our technical competencies, proactive management approach, proven methodologies, committed support and the ability to quickly react to urgent needs make us a valued partner for any kind of Digital Enablement Services, Managed Services, or Business Services.
We believe that the technology and thought leadership that we command in the industry is the direct result of the kind of people we have been able to attract, to form this organization (you are one of them!).
Our workforce consists of 1000+ highly skilled professionals, with leadership and senior management executives who have graduated from Ivy League Universities like MIT, Wharton, IITs, IIMs, and BITS and with rich work experience in some of the biggest companies in the world.
Wissen Technology has been certified as a Great Place to Work®. The technology and thought leadership that the company commands in the industry is the direct result of the kind of people Wissen has been able to attract. Wissen is committed to providing them the best possible opportunities and careers, which extends to providing the best possible experience and value to our clients.
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Role Overview
As a Software Engineer, you will build and maintain features across our SaaS platform. You will work on well-scoped tasks and features, collaborate closely with senior engineers, and grow your skills in software design, cloud-native development, and modern engineering practices. This role is a great fit for engineers who have solid programming fundamentals, are curious and quick to learn, and take pride in writing quality code. You will be supported and mentored while taking on increasing ownership over time.
Required Qualifications
Bachelor’s or Master’s degree in Computer Science or a related discipline.·
5–8 years of software engineering experience building production-grade applications.
Strong experience building and operating cloud-native SaaS or web applications.
Solid understanding of software design, distributed systems, and modern engineering practices.
Proven ability to own and deliver complex features independently.
Experience debugging and resolving performance, scalability, and reliability issues.
What We Look For
Strong programming fundamentals and a quality mindset.
Curiosity and a strong desire to learn and grow.
Ability to deliver well-scoped tasks reliably.
Good problem-solving and debugging skills.
Collaboration and communication skills.
Ownership and accountability for the work you do.
Passion for building software and continuous learning.
Amura’s Vision
We believe that the most under-appreciated route to releasing untapped human potential is to build a healthier body, and through which a better brain. This allows us to do more of everything that is important to each one of us.
Billions of healthier brains, sitting in healthier bodies, can take up more complex problems that defy solutions today, including many existential threats, and solve them in just a few decades.
Billions of healthier brains will make the world richer beyond what we can imagine today. The surplus wealth, combined with better human capabilities, will lead us to a new renaissance, giving us a richer and more beautiful culture.
These healthier brains will be equipped with deeper intellect, be less acrimonious, more magnanimous, and have a kinder outlook on the world, resulting in a world that is better than any previous time.
We find this vision of the future exhilarating. Our hopes and dreams are to create this future as quickly as possible and ensure that it is widely distributed and optimized to maximize all forms of human excellence.
Role Overview
We are looking for a highly skilled Senior DevOps Engineer (AI-Native Infrastructure & Platform Engineering) with deep expertise in AWS cloud infrastructure, automation, AI infrastructure operations, and modern DevOps/SRE practices.
This role goes beyond traditional DevOps and requires a seasoned specialist capable of building and operating AI-ready infrastructure platforms that support high-throughput APIs, LLM/AI workloads, GPU-based compute, data-intensive systems, real-time inference pipelines, and scalable ML platforms.
You will be responsible for architecting, automating, securing, and optimizing highly scalable and cost-efficient cloud environments that enable high-velocity engineering and AI teams. This is an ideal position for someone who combines technical ownership, an automation-first mindset, and a passion for developer productivity and platform reliability.
Key Responsibilities
Cloud Infrastructure & Platform Engineering (AWS)
- Architect, deploy, and manage highly scalable and secure infrastructure on AWS. Design cloud platforms supporting AI/ML workloads, data pipelines, real-time APIs, and high-concurrency backend systems.
- Hands-on expertise with key AWS services including EC2, ECS/EKS, Lambda, RDS, DynamoDB, S3, VPC, CloudFront, IAM, CloudWatch, and GPU-enabled instances.
- Build and maintain Infrastructure-as-Code (IaC) using Terraform, CloudFormation, or AWS CDK.
- Design multi-AZ and multi-region architectures for high availability and disaster recovery (HA/DR).
- Build reusable platform templates and shared infrastructure modules.
AI/ML Infrastructure & MLOps
- Build and maintain infrastructure for LLM applications, AI inference workloads, model serving platforms, vector databases, and feature stores.
- Support GPU-based workloads and optimize compute/storage usage.
- Enable scalable deployment patterns for AI applications using Kubernetes/EKS. Collaborate with Data Science and ML Engineering teams on model deployment, training/tuning of models, CI/CD for ML systems, experiment environments, and reproducibility.
- Support orchestration and deployment of AI workflows and inference services while implementing observability and reliability for AI pipelines.
CI/CD, Automation & Developer Productivity
- Build and maintain CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, or AWS CodePipeline.
- Automate deployments, environment provisioning, and release workflows.
- Build self-service developer platforms, preview environments, and reusable deployment workflows to improve developer productivity.
- Implement automated patching, scaling, backups, cleanup workflows, and drift detection.
Containers, Kubernetes & Platform Reliability
- Manage Docker-based environments, containerized applications, and optimize workloads using Kubernetes (EKS) or ECS/Fargate.
- Manage autoscaling, cluster health, node pools, ingress, service mesh, and workload isolation.
- Optimize infrastructure for performance, resilience, and cost-efficiency.
- Implement progressive deployment strategies including blue/green, canary, and rolling deployments.
Observability, Incident Response & SRE Practices
- Implement observability stacks using CloudWatch, Prometheus, Grafana, ELK, Datadog, OpenTelemetry, or New Relic.
- Build actionable dashboards and intelligent alerting systems while defining and tracking SLIs, SLOs, and SLAs.
- Lead incident response, root cause analysis, and blameless postmortems to reduce operational toil and improve MTTR.
FinOps, Cost Governance & Security
- Continuously monitor and optimize cloud costs (compute utilization, storage lifecycle, GPU usage, and data transfer) using AWS Cost Explorer, Budgets, Trusted Advisor, CloudHealth, or Kubecost.
- Implement AWS security best practices for IAM, VPCs, security groups, NACLs, encryption, and manage secrets using KMS, SSM Parameter Store, or Vault.
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Collaboration, Leadership & Platform Culture
- Work closely with engineering, AI/ML, QA, product, and operations teams to drive a DevOps, SRE, GitOps, and automation-first culture.
- Mentor junior DevOps and Platform Engineers while creating and maintaining detailed runbooks, architecture diagrams, and platform documentation.
Skills & Qualifications
Must-Have:
- 7+ years of experience in DevOps, SRE, Platform Engineering, or Cloud Infrastructure Engineering.
- Strong expertise in AWS cloud architecture, services, and deep understanding of Kubernetes (EKS), containers, and cloud-native systems.
- Strong Infrastructure-as-Code expertise using Terraform, CloudFormation, or CDK. Strong Linux administration, networking, DNS, routing, and load balancing knowledge. Strong scripting/programming experience in Python, Bash, or Go (preferred). Experience with CI/CD automation, GitOps workflows, and observability platforms supporting scalable production systems.
Preferred / Nice-to-Have:
- Experience with AI/ML infrastructure, MLOps, model serving, vector databases, GPU orchestration, and inference optimization.
- Familiarity with Kafka, Redis, SQS, and event-driven systems.
- Exposure to platform engineering, internal developer platforms, and tools like ArgoCD, Flux, Helm, and OpenTelemetry.
- AWS Certifications: Solutions Architect, DevOps Engineer, or SysOps Administrator. Knowledge of distributed systems and large-scale platform operations.
Preferred / Nice-to-Have:
- Experience with AI/ML infrastructure, MLOps, model serving, vector databases, GPU orchestration, and inference optimization.
- Familiarity with Kafka, Redis, SQS, and event-driven systems.
- Exposure to platform engineering, internal developer platforms, and tools like ArgoCD, Flux, Helm, and OpenTelemetry.
- AWS Certifications: Solutions Architect, DevOps Engineer, or SysOps Administrator. Knowledge of distributed systems and large-scale platform operations.
Here are answers to some questions you may have
Where is your office?
Chennai (Velachery)
Work Model
Work from Office – because great stories are built in person!
Do you have an online presence?
https://amura.ai (we are @AmuraHealth on all social media)
- Linux troubleshooting
- Hands-on AWS
- Production/Application Support
- Bash/Shell/Python
- Monitoring/log analysis
- Incident resolution
- Application deployment/support
- Basic networking and database knowledge
- Production/batch support exposure
- Willingness for rotational weekend/critical production support
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: Linux & 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.
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
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.
Technical Expertise
• Proficiency in Node.js or Python – Hands-on experience with backend development frameworks
and best practices.
• Expertise in SQL/NoSQL Databases – Strong experience with MySQL, PostgreSQL, MongoDB, or
DynamoDB.
• ElasticSearch & API Development – Strong knowledge of REST APIs, ElasticSearch, and high-
availability system design.
• Cloud & DevOps – Hands-on experience with AWS, Kubernetes, Docker, and CI/CD pipelines.
• Data Structures & Algorithms – Strong command over data structures, algorithms, OOD, and
design patterns.
• Version Control & Deployment – Experience with Git, GitHub Actions, and other deployment
systems.
• High-Performance Systems – Implemented solutions that handle high availability, concurrency,
and low-latency requirements.
Site Reliability Engineer (SRE) / DevOps Engineer (Walk-In Drive)
Location: Gurgaon Experience: 3–6 Years
About the Role
We are looking for a hands-on Site Reliability Engineer (SRE) / DevOps Engineer with strong programming and automation skills.
The role will initially involve development and automation work, helping the engineer build a strong understanding of the applications and platform. Over time, the role will expand into broader DevOps and SRE responsibilities, including CI/CD, cloud infrastructure, observability, production reliability, incident management, and operational automation.
The ideal candidate should be comfortable working with both application code and production systems and should use engineering and automation to improve reliability and reduce manual effort.
Key Responsibilities
· Develop and enhance internal applications, automation tools, APIs, utilities, and platform capabilities using Python.
· Write clean, maintainable, testable, and production-ready code.
· Participate in code reviews, debugging, testing, and technical discussions.
· Build, maintain, and improve CI/CD pipelines and automated deployment processes.
· Work with Docker and Kubernetes for application deployment and operations.
· Support on prem and cloud-based application and infrastructure deployments.
· Maintain reliable, scalable, secure, and highly available production environments.
· Implement and manage monitoring, logging, alerting, and observability solutions.
· Contribute to defining and tracking SLIs, SLOs, and error budgets.
· Troubleshoot application and production issues and perform Root Cause Analysis (RCA).
· Identify recurring operational problems and address them through automation and engineering improvements.
· Support incident response, change management, deployment governance, and disaster recovery practices.
· Maintain runbooks, SOPs, incident documentation, and technical documentation.
· Collaborate with Engineering, Product, Platform, Security, Operations, and external teams.
Technical Skills
· Strong hands-on experience with Python for development and automation.
· Experience developing scripts, APIs, integrations, utilities, or backend services.
· Good understanding of software engineering principles, debugging, logging, testing, and exception handling.
· Experience with REST APIs, JSON, Git, pull requests, and code reviews.
· Strong knowledge of Linux/Unix environments and basic Windows administration.
· Good understanding of networking concepts including DNS, TCP/IP, HTTP/HTTPS, load balancing, and firewalls.
· Experience with at least one cloud platform: AWS, Azure, or GCP.
· Hands-on experience with Docker and Kubernetes.
· Experience with CI/CD tools such as GitHub Actions, GitLab CI, Jenkins, Azure DevOps, or equivalent.
· Familiarity with Infrastructure-as-Code tools such as Terraform is preferred.
· Experience with monitoring and observability tools such as Grafana, Prometheus, Power BI, or equivalent.
· Ability to analyze logs, metrics, alerts, and traces for troubleshooting.
· Understanding of SRE concepts including SLIs, SLOs, availability, reliability, error budgets, and RCA.
· Experience with JIRA, ServiceNow, and Confluence is desirable.
Preferred Experience
· 3–6 years of experience in SRE, DevOps, Platform Engineering, Cloud Engineering, or related roles.
· Strong Python development or automation experience.
· Experience supporting applications across development, deployment, and production environments.
· Exposure to cloud-native, distributed, or production-grade systems.
· Understanding of security and compliance best practices.
· Familiarity with AI-assisted engineering tools such as GitHub Copilot, Claude Code, or similar tools.
Soft Skills
· Strong analytical and troubleshooting skills.
· Engineering and automation mindset.
· Good written and verbal communication skills.
· Effective cross-functional collaboration.
· Ownership-driven approach to problem solving.
· Ability to remain structured during production incidents.






