Services Jobs in Hyderabad

SAP BTP Integration & Build Apps Specialist

SACHA Engineering•

Hyderabad

•full time

Job Summary We are seeking a skilled and experienced SAP BTP Integration & Build Apps Specialist to join our team in a hybrid work mode. This role will be pivotal in designing, building, and maintaining integrations and applications on the SAP Business Technology Platform (BTP) , ensuring alignment with business requirements and adherence to security and compliance standards. Key Responsibilities The SAP BTP Integration & Build Apps Specialist will be responsible for a range of tasks including, but not limited to, the design, development, and implementation of SAP BTP -based solutions. This includes building and maintaining CI/CD pipelines , ensuring application stability , and creating comprehensive technical documentation and operational runbooks . The role also involves collaborating with cross-functional teams to ensure seamless integration with existing S/4HANA systems and adherence to audit and compliance requirements. Required Skills & Qualifications SAP BTP : Demonstrated proficiency in utilizing SAP Business Technology Platform for application development and integration. Cloud Foundry : Strong understanding and practical experience with the Cloud Foundry platform. Destination & Connectivity Services : Expertise in configuring and managing Destination & Connectivity Services for secure and reliable data exchange. XSUAA : Proficiency in utilizing XSUAA for authentication and authorization within SAP BTP environments. Cloud Identity Services (IAS/IPS) : Experience with Cloud Identity Services (IAS/IPS) for managing user identities and access. Cloud Connector : Ability to configure and manage the Cloud Connector for hybrid scenarios. CI/CD pipelines : Experience in designing and implementing CI/CD pipelines for automated build, testing, and deployment. Git : Proficient in using Git for version control and collaborative development. SAP Build Apps : Experience in developing applications using SAP Build Apps , including Logic flows & data modeling and UI/UX configuration . Role-based access configuration : Ability to configure role-based access controls to ensure data security and compliance. Mobile/web deployment : Experience in deploying applications to mobile and web environments. OData services : Understanding of OData services for data integration and exchange. REST APIs : Experience working with REST APIs for application integration. CDS exposure (consumption) : Ability to consume CDS (Core Data Services) for data access. ABAP : Familiarity with ABAP programming for custom development and integration. SAP Integration Suite : Experience with SAP Integration Suite for integration scenarios. OAuth2, SAML : Knowledge of OAuth2 and SAML for secure authentication and authorization. Certificates : Ability to manage and configure Certificates for secure communication. Event Mesh : Understanding of Event Mesh for event-driven integration. Build Apps development standards : Adherence to Build Apps development standards for code quality and maintainability. Application stability : Focus on ensuring application stability and performance. Technical documentation : Ability to create clear and concise technical documentation . Operational runbooks : Experience in developing operational runbooks for incident response and troubleshooting. Audit, Compliance, Security standards : Understanding of audit , compliance , and security standards . Clean-core extensibility concepts : Knowledge of Clean-core extensibility concepts . CAP (Cloud Application Programming Model) : Experience with CAP (Cloud Application Programming Model) . S/4HANA business processes : Understanding of S/4HANA business processes , including FI , MM , and SD . SLA : Ability to meet SLA requirements. Experience Required: The ideal candidate will possess 8-15 years of relevant experience in SAP development and integration, demonstrating a strong track record of delivering high-quality solutions. What We Offer Salary: 30 LPA

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

Cyber Security Software Engineer

RLE India Private Limited•

Bengaluru

•full time

Job Summary We are seeking a skilled and motivated Cyber Security Software Engineer to join our team in Bangalore. This role will focus on developing and implementing robust security solutions within our Automotive Embedded Systems . The ideal candidate will possess a strong understanding of cybersecurity principles and a proven ability to design and implement secure software solutions. Key Responsibilities The Cyber Security Software Engineer will be responsible for the following: Designing and implementing secure software solutions for Automotive Embedded Systems . Conducting Threat Analysis to identify potential vulnerabilities and risks. Developing Secure Architecture Designs that incorporate industry best practices. Performing Platform-level Debugging to identify and resolve security-related issues. Implementing Secure Boot mechanisms to ensure the integrity of the system. Developing and implementing Secure Time Validation and Time Tampering Detection mechanisms. Integrating and utilizing Cryptographic Services to protect sensitive data. Working with Trusted Execution Environments to isolate and protect critical code. Developing and maintaining Security Middleware and Security Services . Managing Key Management processes to ensure the confidentiality and integrity of cryptographic keys. Utilizing Trusted Time Sources to ensure accurate and reliable timekeeping. Performing System Hardening to reduce the attack surface of the system. Developing and implementing Security Controls to mitigate identified risks. Ensuring compliance with relevant Automotive Standards . Conducting Penetration Testing to identify vulnerabilities. Ensuring Cybersecurity Compliance with industry regulations. Performing Unit Testing , Integration Testing , and Security Testing to ensure the quality and security of the software. Required Skills & Qualifications The ideal candidate will possess the following skills and qualifications: Strong understanding of Cyber Security principles and best practices. Proficiency in programming languages including C and C++ . Experience with Android and QNX operating systems. Experience with Secure Time/RTC Manager and Timezone management. Knowledge of Real-Time Clock (RTC) and Timezone Management concepts. Experience with Automotive Embedded Systems development. Proven ability in Embedded Software Development . Ability to perform Threat Analysis and identify potential vulnerabilities. Experience in designing Secure Architecture . Proficiency in Platform-level Debugging techniques. Knowledge of Secure Boot mechanisms. Understanding of Secure Time Validation and Time Tampering Detection . Experience with Cryptographic Services and Trusted Execution Environments . Familiarity with Security Middleware and Security Services . Knowledge of Key Management principles. Understanding of Trusted Time Sources . Experience with System Hardening techniques. Familiarity with Platform-level Services . Knowledge of Secure Time and RTC Synchronization . Understanding of Security Controls . Familiarity with Automotive Standards . Experience with Penetration Testing methodologies. Knowledge of Cybersecurity Compliance requirements. Experience with Unit Testing , Integration Testing , and Security Testing . Experience Required: 6 - 8 years of relevant experience. This level of experience indicates a seasoned professional capable of independently designing, developing, and implementing complex security solutions within an embedded systems environment. The candidate should be able to mentor junior engineers and contribute to the overall security posture of the organization. What We Offer Salary: