Devops Jobs in Hyderabad

Scrum Master

RLE India Private Limited•

Pune

•full time

Job Summary We are seeking a skilled and experienced Scrum Master to join our dynamic team in Pune. This role is crucial for ensuring the successful delivery of high-quality software solutions through the effective application of Agile principles and practices. The ideal candidate will possess a strong understanding of the software development lifecycle and a proven ability to facilitate Scrum events and remove impediments for development teams. Key Responsibilities The Scrum Master will be responsible for guiding and coaching development teams on the use of Scrum , ensuring they adhere to Agile values and principles. This includes facilitating Scrum ceremonies, such as sprint planning, daily Scrum , sprint review, and sprint retrospective. The role also involves identifying and removing impediments that hinder the team's progress, fostering a collaborative and self-organizing environment. Required Skills & Qualifications Understanding of Software Development Lifecycle (SDLC): A comprehensive understanding of the various phases of the software development lifecycle, from inception to deployment and maintenance. Agile Engineering Practices: Demonstrated proficiency in Agile methodologies, particularly Scrum , and the ability to coach teams on their effective implementation. Common Engineering Workflows: Familiarity with standard engineering workflows, including version control, code review, and continuous integration. Web Application Technologies: Knowledge of technologies used in web application development, including Angular . Mobile Application Technologies: Understanding of technologies used in mobile application development. Desktop Application Technologies: Understanding of technologies used in desktop application development, including C# , .NET , and WPF . Ability to Work with Technical Leads: Proven ability to collaborate effectively with technical leads to ensure alignment on technical direction and execution. DevOps Tools & Workflows: Experience with DevOps tools and workflows, including CI/CD . Backlog Tools: Proficiency in using Backlog tools such as Jira and Azure Boards to manage product and sprint backlogs. Communication Skills: Excellent verbal and written communication skills, with the ability to clearly and concisely convey technical information to both technical and non-technical audiences. English: Fluency in English, both written and spoken. Estimation, Dependencies, Risks: Ability to facilitate discussions and guide teams in estimating tasks, identifying dependencies, and assessing risks. Metrics: Understanding of key Scrum metrics, including Velocity , Burndown , and Flow Efficiency . Scrum Artifacts: Deep understanding of Scrum artifacts, including the Product Backlog , Sprint Backlog , and Increment . Technical Execution & Craftsmanship: Appreciation for Technical Craftsmanship principles, Clean Code , and Maintainability . Testing Approach & System Stability: Understanding of testing approaches and their impact on System Stability . System Integration Concepts: Knowledge of API and Cloud concepts and System Integration concepts. Experience Required: The ideal candidate will have 4-6 years of experience in a related role, demonstrating a solid foundation in software development and Agile practices. This level of experience is expected to provide a strong understanding of team dynamics and the ability to effectively facilitate Scrum events and remove impediments. 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 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