Kubernetes Jobs in Chennai

Platform Engineering Engineer 3

SACHA Engineering•

Chennai

•full time

Job Summary We are seeking a highly skilled and motivated Platform Engineering Engineer 3 to join our growing team. This role will be instrumental in building and maintaining our platform, ensuring its reliability, scalability, and security. The ideal candidate will possess a strong understanding of cloud technologies, infrastructure automation, and distributed systems. This is a hybrid role. Key Responsibilities The Platform Engineering Engineer 3 will be responsible for designing, building, and maintaining robust and scalable platform infrastructure. This includes automating infrastructure deployments, monitoring system performance, and troubleshooting issues to ensure high availability and optimal performance. The role requires a proactive approach to identifying and resolving potential problems before they impact users. Required Skills & Qualifications Programming Languages: Proficiency in Java , Python , and Go is essential. Experience with Bash scripting for automation and system administration tasks is also required. Cloud Platforms: Demonstrated experience with cloud platforms including AWS , GCP , and Azure . Containerization & Orchestration: Strong understanding and practical experience with Docker and Kubernetes for containerization and orchestration. Monitoring & Observability: Expertise in using monitoring and observability tools such a Prometheus , Grafana , ELK , OpenSearch , Datadog , OpenTelemetry , Jaeger , and Zipkin . Networking Fundamentals: Solid understanding of networking concepts including DNS , LB , TCP/IP , VPC/subnet design , and Security groups . Security & Compliance: Experience with IAM , Secrets Management using tools like Vault and KMS , and implementing Patching and Vuln Scanning procedures. Platform Reliability & Performance: A focus on Platform Availability and a proven ability to perform Runtime Performance Tuning . Infrastructure Automation: Expertise in Infrastructure as Code ( IaC ) principles and tools. Continuous Integration & Continuous Delivery: Experience with CI/CD pipelines and automation. Cloud Architecture: Ability to design and implement Cloud Architecture solutions. Site Reliability Engineering (SRE): Familiarity with SRE principles and practices. Runtime Optimization: Ability to perform Runtime Optimization for distributed systems. Distributed Systems: Experience with Distributed Backend Systems . AI-augmented Platform Operations: Experience with AI-augmented Platform Operations . Analytical Skills: Strong Analytical Skills for problem-solving and data-driven decision-making. Problem-Solving Skills: Excellent Problem-Solving Skills to quickly identify and resolve issues. Communication Skills: Effective Communication Skills to collaborate with cross-functional teams. Any Degree is required. 6 - None years of experience are required. This indicates a mid-level seniority with expectations of independent work and mentorship of junior team members. What We Offer We offer a competitive compensation package.

AI Build Engineer

RLE India Private Limited•

Bengaluru

+2 More

Other Locations2 cities

Chennai

Hyderabad

•full time

Job Summary We are seeking a skilled and experienced AI Build Engineer to join our dynamic team. This role will be responsible for building and deploying cutting-edge AI solutions, leveraging a variety of technologies and methodologies. The ideal candidate will possess a strong foundation in software engineering principles and a passion for AI innovation. Key Responsibilities The AI Build Engineer will be responsible for the design, development, and implementation of AI applications. This includes collaborating with cross-functional teams to define requirements, designing and building robust and scalable AI solutions, and ensuring the quality and reliability of deployed AI models. The role also involves continuous monitoring and optimization of AI systems to ensure peak performance and alignment with business objectives. Required Skills & Qualifications Programming Languages: Proficiency in multiple programming languages including Python , JavaScript , TypeScript , and C# . This includes the ability to write clean, efficient, and well-documented code. Large Language Models (LLMs): A strong understanding of LLMs and their application in various use cases. Retrieval-Augmented Generation (RAG): Experience with RAG techniques to enhance the capabilities of LLMs . Prompt Engineering: Expertise in Prompt Engineering to design effective prompts for LLMs . Vector Databases: Familiarity with Vector Databases and their use in storing and retrieving vector embeddings. Agentic AI: Knowledge of Agentic AI principles and their application in building autonomous agents. Cloud Platforms: Experience with cloud platforms such as Azure and AWS , including Azure AI Services , Azure OpenAI , AWS Bedrock , and Vertex AI . Containerization & Orchestration: Proficiency in Docker and Kubernetes for containerizing and orchestrating AI applications. DevOps & CI/CD: Experience with DevOps practices and CI/CD pipelines using tools like GitHub Actions and Azure DevOps . MLOps: Understanding of MLOps principles and best practices for managing the ML lifecycle. AI Application Integration: Ability to integrate AI applications into existing systems and workflows. Testing & Monitoring: Experience with AI-infused testing , Monitoring , and Observability tools and techniques. Governance: Understanding of Governance principles related to AI systems. API & Microservices: Experience with API development and Microservices architectures. Additional Skills: Familiarity with MCP , Playwright , and AI copilots . Qualifications: Possession of AI/Cloud certifications such as Azure AI Engineer or AWS ML is highly desirable. Experience Required: We are seeking candidates with 5-10 years of relevant experience in software engineering and AI development. This level of experience should demonstrate a proven ability to design, build, and deploy complex AI solutions in a production environment. What We Offer The role is onsite .

AI Build Engineer (GenAI / Agentic AI / AI Automation)

RLE India Private Limited•

Bengaluru

+2 More

Other Locations2 cities

Chennai

Hyderabad

•Full-time

Job Summary We are seeking a skilled and experienced AI Build Engineer to join our growing team. This role will focus on the development and implementation of cutting-edge AI solutions, specifically within the realms of GenAI , Agentic AI , and AI Automation . The ideal candidate will possess a strong foundation in software engineering principles and a passion for leveraging AI to solve complex business challenges. This position is located in Bengaluru, Chennai, or Hyderabad. Key Responsibilities The AI Build Engineer will be responsible for designing, building, and deploying AI -powered applications and systems. This includes collaborating with cross-functional teams to define requirements, developing robust and scalable solutions, and ensuring the ongoing performance and reliability of deployed systems. The role demands a proactive approach to problem-solving and a commitment to delivering high-quality AI solutions. Required Skills & Qualifications Programming Languages: Proficiency in multiple programming languages is essential, including Python , JavaScript , TypeScript , and C# . Experience should demonstrate the ability to write clean, efficient, and well-documented code. Large Language Models (LLMs): A strong understanding of LLMs and their application in various use cases. Retrieval Augmented Generation (RAG): Experience implementing RAG architectures to enhance LLM capabilities with external knowledge sources. Prompt Engineering: Expertise in crafting effective prompts to elicit desired responses from LLMs . Vector Databases: Familiarity with vector databases and their use in storing and querying vector embeddings. Agentic AI: Experience in developing and deploying Agentic AI systems, leveraging autonomous agents to perform complex tasks. Model Context Protocol (MCP): Understanding of MCP and its role in managing AI model context. Testing & Automation: Experience with Playwright and AI-infused testing solutions to ensure the quality and reliability of AI systems. Frameworks & Libraries: Proficiency in utilizing frameworks and libraries such as LangChain and LangGraph for building LLM -powered applications. Cloud Platforms: Experience with Azure OpenAI , AWS Bedrock , and Vertex AI for developing and deploying AI models. Containerization & Orchestration: Solid understanding of Docker and Kubernetes for containerizing and orchestrating AI applications. DevOps & CI/CD: Experience with GitHub Actions and Azure DevOps for implementing CI/CD pipelines. MLOps: Knowledge of MLOps principles and practices for managing the entire ML lifecycle. AI Copilots: Familiarity with AI copilots and their integration into development workflows. Autonomous Agents: Experience in designing and implementing autonomous agents for various tasks. API & Microservices: Experience designing and building APIs and microservices for AI applications. Infrastructure: Understanding of monitoring , observability , and governance best practices for AI systems. Security: Commitment to building secure and responsible AI solutions. Analytical & Problem-Solving Skills: Strong analytical skills and problem-solving skills to effectively troubleshoot and resolve issues. Communication Skills: Excellent communication skills to effectively collaborate with cross-functional teams. Experience Required: 5 - 10 years of experience in software engineering with a focus on AI development. This level of experience is expected to demonstrate a proven ability to design, build, and deploy complex AI systems. The candidate should be comfortable working independently and as part of a team, and possess a strong understanding of software development best practices. Qualifications: AI/Cloud certifications ( Azure AI Engineer , AWS ML , etc.) are preferred. What We Offer Salary:

AI Build Engineer

RLE India Private Limited•

Bengaluru

+2 More

Other Locations2 cities

Chennai

Hyderabad

•full time

Job Summary We are seeking a skilled and motivated AI Build Engineer to join our growing team. This role will focus on building, deploying, and maintaining robust and scalable AI solutions. The ideal candidate will possess a strong foundation in software engineering principles and a passion for leveraging cutting-edge AI technologies. Key Responsibilities The AI Build Engineer will be responsible for the following: Developing and implementing AI models and applications using various programming languages and frameworks. Building and maintaining robust CI/CD pipelines for automated testing, building, and deployment of AI models. Ensuring the quality and reliability of AI solutions through rigorous testing and monitoring . Collaborating with cross-functional teams to define, design, and ship new features. Implementing and maintaining governance policies for AI models. Required Skills & Qualifications To be successful in this role, candidates must possess the following skills and qualifications: Proficiency in programming languages including Python , JavaScript , TypeScript , and C# . Experience with large language models ( LLMs ) and related techniques such as RAG (Retrieval Augmented Generation) and Prompt Engineering . Solid understanding of vector databases and their application in AI systems. Familiarity with Agentic AI concepts and implementation. Experience with Model Context Protocol (MCP) . Experience with testing frameworks such as Playwright . Experience with frameworks such as LangChain and LangGraph . Experience with cloud-based AI services including Azure OpenAI , AWS Bedrock , and Azure AI Services , and Vertex AI . Strong experience with containerization technologies such as Docker and orchestration platforms like Kubernetes . Experience with version control systems such as GitHub Actions and Azure DevOps . Knowledge of MLOps principles and practices. Familiarity with AI copilots and Autonomous agents . Experience with AI-infused testing solutions . Understanding of API design and development. Experience building Microservices architectures. Strong Analytical Skills , Problem-Solving Skills , and Communication Skills . Experience Required: 5 - 10 years of experience in software engineering with a focus on AI/ML. This level of experience indicates a seasoned professional capable of independently designing, developing, and deploying complex AI solutions. The candidate should be comfortable working in a fast-paced environment and collaborating with a diverse team of engineers and researchers. What We Offer Salary:

Google Cloud Engineer - SSE

SACHA Engineering•

Bengaluru

+3 More

Other Locations3 cities

Pune

Chennai

Hyderabad

•full time

Job Summary We are seeking a highly skilled and motivated Google Cloud Engineer - SSE to join our growing team. This is a hybrid role requiring a blend of hands-on technical expertise and collaborative teamwork. The ideal candidate will possess a strong foundation in cloud technologies, particularly within the Google Cloud Platform , and a proven ability to design, implement, and maintain robust and scalable cloud solutions. Key Responsibilities The Google Cloud Engineer - SSE will be responsible for a range of tasks related to the design, implementation, and maintenance of our Google Cloud infrastructure. This includes automating infrastructure provisioning, optimizing cloud resources for cost and performance, and ensuring the reliability and security of our cloud-based applications and services. Required Skills & Qualifications Education: A Bachelor’s degree in computer science or a related field, or a higher degree, is required. A minimum of 3 years of relevant experience is expected. Experience: 6 - 10 years of experience in a related field is required. This level of experience indicates a strong understanding of cloud technologies and a proven ability to work independently and as part of a team. DevOps: Demonstrated proficiency in DevOps principles and practices, with a focus on automation and continuous delivery. Google Kubernetes Engine (GKE): Extensive experience with GKE , including cluster configuration, deployment, and management. Infrastructure-as-Code: Strong understanding and practical experience with Infrastructure-as-Code methodologies and tools. Terraform: Expertise in using Terraform to provision and manage Google Cloud resources. Deployment Manager: Familiarity with Deployment Manager for automated deployment of Google Cloud resources. CI/CD: Deep understanding of CI/CD pipelines and experience with tools such as Cloud Build , Jenkins , and GitHub Actions . Kubernetes: Solid foundation in Kubernetes concepts, including Deployments , Services , and Autoscaling . Programming/Scripting: Proficiency in Python and Bash scripting for automation and system administration tasks. Version Control: Experience with GitOps principles and tools like ArgoCD and Helm . Cloud Governance: Knowledge of Cloud Governance best practices and experience implementing policies and controls. Cost Management: Ability to analyze and optimize Cloud costs, ensuring efficient resource utilization. Compliance: Understanding of Compliance requirements and experience implementing security measures to meet regulatory standards. Cloud Migration: Experience with Cloud Migration strategies and methodologies. System Reliability: Strong focus on System Reliability and experience designing and implementing highly available and resilient systems. High Availability & Redundancy: Expertise in designing for High Availability and Redundancy . Backup Strategies: Experience developing and implementing effective Backup Strategies . Proactive Monitoring: Ability to implement Proactive Monitoring solutions to identify and address potential issues before they impact users. Process Efficiencies: A commitment to identifying and implementing Process Efficiencies to improve operational effectiveness. Analytical Skills: Strong Analytical Skills for problem-solving and data-driven decision-making. Problem-Solving Skills: Excellent Problem-Solving Skills with the ability to troubleshoot complex technical issues. Communication Skills: Effective Communication Skills for collaborating with cross-functional teams and communicating technical concepts to both technical and non-technical audiences. Teamwork: Demonstrated ability to work effectively as part of a Teamwork environment. What We Offer Salary: ₹15 LPA - ₹20 LPA

Senior DevOps Engineer – Cloud Platform (AWS)

RLE India Private Limited•

Chennai

•full time

Job Summary We are seeking a highly skilled and experienced Senior DevOps Engineer to join our team in Bangalore. This role will focus on the design, implementation, and maintenance of our AWS -based cloud platform. The ideal candidate will possess a strong understanding of DevOps principles, Platform Engineering practices, and SRE methodologies, with a proven ability to build and operate robust, scalable, and secure cloud infrastructure. Key Responsibilities The Senior DevOps Engineer will be responsible for ensuring the reliability, security, and performance of our cloud platform. This includes automating infrastructure provisioning, implementing continuous integration and continuous delivery ( CI/CD ) pipelines, and proactively identifying and resolving operational issues. The role requires a deep understanding of cloud security best practices and a commitment to maintaining a secure and compliant environment. Required Skills & Qualifications DevOps : Demonstrated expertise in DevOps methodologies, including automation, continuous integration, continuous delivery, and infrastructure as code. Platform Engineering : Experience in designing and building scalable and resilient cloud platforms, with a focus on automation and self-service capabilities. SRE : Familiarity with SRE principles and practices, including monitoring, alerting, incident response, and post-mortem analysis. AWS : Extensive experience with AWS services, including EC2 , S3 , RDS , ElastiCache , Amazon EKS , MSK , Elasticsearch , and OpenSearch . Kubernetes : Proficiency in deploying and managing applications using Kubernetes . Terraform : Strong experience in infrastructure as code using Terraform . AWS CDK : Ability to utilize AWS CDK for defining and provisioning cloud infrastructure. Ansible : Experience with Ansible for configuration management and automation. Kafka : Understanding of Kafka and MSK for distributed streaming. Datadog , Prometheus , Grafana : Experience with monitoring and observability tools such as Datadog , Prometheus , and Grafana . Cloud Security : Solid understanding of Cloud Security principles, including IAM and Compliance . VPC , Subnets , Routing : Knowledge of VPC configuration, Subnets , and Routing . Security : Strong understanding of Security best practices. Analytical Skills : Ability to analyze complex data and identify trends. Problem-Solving Skills : Proven ability to troubleshoot and resolve technical issues. Communication Skills : Excellent written and verbal communication skills. Experience Required: 10 - 10 years of experience in a DevOps or related role. This level of experience indicates a senior-level expectation, requiring a candidate who can independently lead projects, mentor junior team members, and contribute to the overall DevOps strategy. What We Offer Salary:

Platform Engineering Engineer D

RLE India Private Limited•

Chennai

•full time

Job Summary We are seeking a skilled and motivated Platform Engineering Engineer D to join our growing IT / Technology team. This role will focus on building and maintaining robust and scalable platforms to support our evolving business needs. The ideal candidate will possess a strong foundation in cloud technologies, automation, and a commitment to delivering high-quality solutions. Key Responsibilities The specific responsibilities for this role will be determined based on the needs of the business and will evolve over time. We expect the successful candidate to be adaptable and willing to take on new challenges as they arise. Required Skills & Qualifications To be considered for this position, candidates must demonstrate proficiency in the following areas: Programming: Demonstrated experience with Python for scripting, automation, and application development. Infrastructure as Code: Expertise in TERRAFORM for defining and managing infrastructure through code, ensuring consistency and repeatability. Configuration Management: Strong understanding and practical experience with Ansible for automating configuration management and application deployment. Cloud Platforms: Proven ability to work with and deploy solutions on major cloud platforms including AWS , Azure , and GCP . Containerization & Orchestration: Solid experience with Kubernetes and Openshift for container orchestration and management. DevOps Practices: A deep understanding of DevOps principles and experience implementing CI/CD pipelines. Monitoring & Observability: Familiarity with monitoring and observability tools such as Dynatrace , Prometheus , and Grafana . Version Control: Proficiency in using GitHub for version control and collaborative development. Operating Systems: Strong working knowledge of Linux environments. Networking: Understanding of Network Protocols & Standards . Scripting: Ability to write and maintain effective Scripting solutions. Problem Solving: Exceptional Problem Solving skills with a demonstrated ability to diagnose and resolve complex technical issues. Technical Troubleshooting: Adept at Technical Troubleshoot and root cause analysis. Communication Skills: Excellent Communication Skills , both written and verbal, to effectively collaborate with cross-functional teams. Services: Experience managing and supporting Services . Cloud Infrastructure: Solid understanding of Cloud Infrastructure principles and best practices. Storage Capacity Management: Experience with Storage Capacity Management . VMware: Familiarity with VMware virtualization technologies. Tekton: Experience with Tekton for CI/CD. Education: A Bachelor's degree in Computer Science , Information Technology , or a related field is required. Experience: A minimum of 6 years of experience in a related engineering role is expected. This level of experience should demonstrate a proven ability to design, implement, and maintain complex systems in a fast-paced environment. What We Offer Salary:

Back-end Software Development Engineer

RLE India Private Limited•

Chennai

•full time

Job Summary We are seeking a skilled Back-end Software Development Engineer to join our growing team. This role is ideal for a highly motivated individual with a strong foundation in back-end development and a passion for leveraging cutting-edge technologies to build scalable and robust solutions. Key Responsibilities The responsibilities of this role will encompass the design, development, and maintenance of our back-end systems. You will be responsible for ensuring the reliability, performance, and security of our applications. Required Skills & Qualifications Full Stack Java Developer : Demonstrated proficiency in Java development, encompassing both front-end and back-end aspects of application development. GCP : Experience with Google Cloud Platform (GCP) services, including deployment, scaling, and management of applications within the GCP environment. Cursor AI : Familiarity with Cursor AI and its application in software development workflows. Open Code AI : Understanding of Open Code AI principles and their implementation in code generation and analysis. Gen AI : Knowledge of Generative AI concepts and their application in software development. Big Query : Expertise in utilizing BigQuery for data warehousing, querying, and analysis. Jira : Proficiency in using Jira for project management, issue tracking, and agile development workflows. Java : Strong understanding of Java programming language and its core principles. Spring Boot : Experience with Spring Boot framework for building stand-alone and production-ready Spring-based applications. Spring MVC : Knowledge of Spring MVC for developing web applications. API Design : Ability to design and implement robust and scalable APIs. REST : Experience with REST ful API design and implementation. GraphQL : Familiarity with GraphQL for efficient data fetching and manipulation. GKE : Experience with Google Kubernetes Engine ( GKE ) for container orchestration. Cloud Run : Understanding of Cloud Run for deploying and managing containerized applications. Pub/Sub : Knowledge of Pub/Sub for asynchronous messaging and event-driven architectures. IAM : Experience with Identity and Access Management ( IAM ) principles and implementation. PostgreSQL : Strong understanding of PostgreSQL database management system. Cloud SQL : Experience with Cloud SQL for managing relational databases in the cloud. Query Tuning : Ability to optimize database queries for performance and efficiency. Replication : Understanding of database replication techniques for high availability and disaster recovery. Indexing : Knowledge of database indexing strategies for improved query performance. BigData : Experience with BigData technologies and processing large datasets. Dataflow : Familiarity with Dataflow for stream and batch data processing. Spark : Experience with Spark for distributed data processing and analytics. Vertex AI : Understanding of Vertex AI for machine learning model deployment and management. LLM APIs : Knowledge of Large Language Model ( LLM ) APIs and their integration into applications. CI/CD : Experience with Continuous Integration and Continuous Delivery ( CI/CD ) pipelines. Docker : Proficiency in using Docker for containerization and application packaging. Kubernetes : Strong understanding of Kubernetes for container orchestration and management. Problem-Solving Skills : Demonstrated ability to analyze complex problems and develop effective solutions. Communication Skills : Excellent written and verbal communication skills for collaborating with team members and stakeholders. Qualifications : A Bachelor's Degree is required. Experience Required : 6 years of experience is preferred. The ideal candidate will possess a proven track record of success in back-end development and a strong understanding of software engineering best practices. What We Offer Salary :

Software Engineer (2) - Commodity Engineer 0

RLE India Private Limited•

Chennai

•full time

Job Summary We are seeking two experienced Software Engineers to join our team in Bangalore. This role focuses on the development and maintenance of our Pega platform, with a strong emphasis on Commodity Engineer principles. The ideal candidate will possess a strong foundation in software engineering principles and a passion for building robust and scalable solutions. Key Responsibilities This role requires a high level of proficiency in designing, developing, and implementing solutions within the Pega environment. You will be responsible for the entire software development lifecycle, from requirements gathering to deployment and ongoing support. A key aspect of this role will be leveraging Automation Tools and DevOps Practices to ensure efficient and reliable delivery of high-quality software. Required Skills & Qualifications Education: A Bachelor's Degree is required. Experience: A minimum of 6-8 years of experience in software engineering is expected. This level of experience indicates a proven ability to independently design, develop, and implement complex software solutions, as well as mentor junior team members. Core Technologies: Pega and Pega PRPC Proficiency: Demonstrated expertise in the Pega platform, including Pega Constellation , Ruleset Strategy , Case Architecture , and Integration Architecture . Programming Languages: Strong proficiency in Python , C# , and JavaScript . .NET Development: Experience with .NET Developer , .Net Framework . RESTful Services, JSON, XML, HTTP, API: Ability to design and consume RESTful Services and work with data formats like JSON and XML . Cloud Technologies: Google Cloud Platform: Familiarity with Google Cloud Platform services. Cloud-Native Deployments: Experience with Cloud-Native Deployments , Kubernetes , AKS , and EKS . DevOps & Automation: DevOps Practices: Solid understanding of DevOps Practices , including CI/CD Pipelines and Release Governance . Automation Frameworks: Experience with Automation Frameworks . Pipeline Deployments: Ability to manage Pipeline Deployments and adhere to Merge Governance best practices. Data & Architecture: Data Model: Strong understanding of Data Model concepts. Microservices Architecture: Experience with Microservices Architecture . AI & Machine Learning: AI: Basic understanding of AI principles. GenAI: Exposure to GenAI concepts. Agentic AI: Familiarity with Agentic AI . Domain Knowledge: Banking, Financial Services: Understanding of Banking and Financial Services concepts, including Disputes , Cards , Payments , and Lending . Pega Smart Disputes: Experience with Pega Smart Disputes . Compliance, Regulatory Considerations: Awareness of Compliance and Regulatory Considerations . Other Skills: Analytical Skills: Strong Analytical Skills for problem-solving and data analysis. Problem-Solving Skills: Excellent Problem-Solving Skills to identify and resolve complex technical issues. Communication Skills: Effective Communication Skills to collaborate with cross-functional teams. What We Offer Salary:

Software Engineer (3) - Core Senior Engineer

RLE India Private Limited•

Chennai

•full time

Job Summary We are seeking a highly skilled and experienced Software Engineer to join our core team. This is a senior-level role requiring a deep understanding of software development principles and a proven ability to design, develop, and deploy scalable and reliable applications. The ideal candidate will possess a strong background in cloud technologies and a passion for building innovative solutions. Key Responsibilities This role will be responsible for the full software development lifecycle, from design and implementation to testing and deployment. The candidate will collaborate with cross-functional teams to deliver high-quality software solutions that meet business requirements. Required Skills & Qualifications Education: A Bachelor's Degree is required. Experience: A minimum of 10 years of experience in software engineering is required. This level of experience indicates a seasoned professional capable of leading technical initiatives and mentoring junior engineers. Programming Languages: Proficiency in Java is essential. Frameworks & Technologies: Demonstrated experience with Spring Boot for building robust and scalable applications. Cloud Computing: Extensive experience with GCP (Google Cloud Platform), including Cloud Run for containerized application deployment. Containerization & Orchestration: Strong understanding of containerization technologies such as Docker and orchestration platforms like Kubernetes , GKE , and OpenShift . Experience with Helm for managing Kubernetes deployments is also required. CI/CD & DevOps: Solid experience with CI/CD pipelines, including tools like Tekton , Argo CD , and GitHub Actions . Familiarity with GitOps principles is a plus. Frontend Development: Experience with Angular for building modern user interfaces. API Development: Proven ability to design and implement REST APIs and Microservices architectures. Integration Patterns: Knowledge of Enterprise Integration Patterns for building loosely coupled and scalable systems. Data Management: Experience with relational databases such as AlloyDB and Cloud SQL for PostgreSQL . Cloud Security: Strong understanding of cloud security principles, including IAM , Service Accounts , Workload Identity Federation , Secret Manager , External Secrets , and Least-Privilege Access Controls . Container Security: Experience with Artifact Registry , Container Security , Binary Authorization , and Vulnerability Scanning . Deployment & Monitoring: Proficiency in Secure Deployment Practices , Cloud Logging , Cloud Monitoring , Prometheus , and Dynatrace/Grafana . Operational Skills: Ability to perform Root-Cause Analysis and implement effective Alerting systems. Infrastructure as Code: Experience with Terraform for managing infrastructure as code. Analytical Skills: Strong Analytical Skills for problem-solving and decision-making. Problem-Solving Skills: Excellent Problem-Solving Skills to identify and resolve complex technical challenges. Communication Skills: Effective Communication Skills for collaborating with cross-functional teams and communicating technical concepts clearly. Networking: Understanding of Application Ingress/Egress , Load Balancing , API Routing , Shared VPC , Private Service Connect , Firewall Rules , and DNS . Connectivity: Experience with Private Connectivity and Cross-Project Communication .