Ai Build Engineer Jobs

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:

CAE Analyst

RLE India Private Limited•

Chennai

•Full-time

CAE Analyst Job Description Job Summary We are seeking a skilled and experienced CAE Analyst to join our team in Chennai. This role is crucial for supporting our Automotive / Mechanical Engineering initiatives, ensuring the quality and durability of our components and systems. Key Responsibilities The CAE Analyst will be responsible for performing a wide range of CAE simulations and analyses to support product development and validation. This includes, but is not limited to, conducting structural analysis , stress analysis , and fatigue life prediction . The role will also involve root cause analysis and failure analysis to identify and resolve potential issues. The analyst will work closely with design and validation teams to ensure that designs meet performance and durability requirements. Required Skills & Qualifications The ideal candidate will possess a strong foundation in Mechanical Engineering and a proven ability to apply CAE principles to solve real-world engineering problems. A B.E / B.Tech / M.E / M.Tech degree is required. Non-linear FE analysis: Proficiency in performing advanced finite element analyses, including non-linear simulations to accurately predict component behavior under complex loading conditions. Abaqus: Demonstrated experience using Abaqus for conducting FE simulations. FE model building: Ability to create accurate and efficient FE models representing complex geometries and boundary conditions. Meshing: Expertise in generating high-quality meshes using industry-standard tools. HyperMesh: Experience utilizing HyperMesh for efficient mesh generation and model preparation. ANSA: Familiarity with ANSA for pre- and post-processing of FE models. Fatigue life prediction: Ability to perform fatigue life prediction using established methodologies and software. FEMFAT: Experience with FEMFAT for fatigue analysis and damage assessment. Structural analysis: A strong understanding of structural analysis principles and their application to automotive components. Stress analysis: Ability to perform detailed stress analysis to identify areas of high stress concentration and potential failure. Material modeling: Knowledge of material modeling techniques and their impact on simulation results. Contact definitions: Ability to accurately define and implement contact definitions in FE models. Reliability assessments: Experience in performing reliability assessments to evaluate the long-term performance of components. Durability assessments: Ability to conduct durability assessments to ensure components can withstand expected usage conditions. Root cause analysis: Proven ability to perform root cause analysis to identify the underlying causes of failures. Failure analysis: Experience in conducting failure analysis to determine the mechanisms of failure. Automotive engineering: A solid understanding of Automotive engineering principles and practices. Quality processes: Familiarity with quality processes and their application to product development. Robust design methodologies: Knowledge of robust design methodologies to create designs that are insensitive to variations in manufacturing and operating conditions. Manufacturing best practices: Understanding of manufacturing best practices and their impact on component performance. Transmission & driveline systems: Familiarity with Transmission & driveline systems and their components. Gears, Shafts, Clutches, Differentials, Propshafts, Half-shafts, Bearings: Knowledge of the design and analysis of these key components. HyperWorks: Experience with HyperWorks for CAE simulation and analysis. Fatigue life/Damage assessment: Ability to perform fatigue life/Damage assessment to predict component lifespan. Boundary conditions: Ability to accurately define and apply appropriate boundary conditions in FE models. Dynamic loading scenarios: Experience in simulating dynamic loading scenarios to evaluate component response to transient loads. Gear strength: Ability to assess gear strength and durability. Shaft durability: Ability to assess shaft durability under various loading conditions. Road load data: Experience in utilizing road load data for simulation. Simulation load cases: Ability to develop and apply appropriate simulation load cases . Physical test data: Ability to correlate simulation results with physical test data . Refine models: Ability to refine models based on simulation results and experimental data. Material properties: Understanding of material properties and their impact on simulation results. Manufacturing processes: Familiarity with manufacturing processes such as Forging, Casting, and Heat treatment . Component durability: Ability to assess component durability under various operating conditions. CAE simulation tools: Proficiency in using various CAE simulation tools . Customer usage profiles: Ability to incorporate customer usage profiles into simulation models. Duty cycles: Ability to define and apply appropriate duty cycles in simulations. Design robustness: Ability to assess and improve design robustness . DFMEA: Familiarity with DFMEA (Design Failure Mode and Effects Analysis). DVP&R: Understanding of DVP&R (Design Verification Plan and Release). Experience Required: The role requires 4 - 9 years of relevant experience in CAE analysis, preferably within the Automotive or Mechanical Engineering industry. Candidates with a strong track record of solving complex engineering problems and delivering high-quality results are highly encouraged to apply. What We Offer Salary: ₹10 LPA - ₹12 LPA

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

Power Platform Software Engineer

RLE India Private Limited•

Chennai

•full time

Job Summary We are seeking a skilled Power Platform Software Engineer to join our IT / Technology team. This role will focus on leveraging the capabilities of the Power Platform to build and maintain robust, efficient, and scalable solutions. The ideal candidate will possess a strong foundation in software development principles and a passion for utilizing innovative technologies to solve complex business challenges. Key Responsibilities The Power Platform Software Engineer will be responsible for the full lifecycle of application development, from initial design and development to testing, deployment, and ongoing support. This includes collaborating with stakeholders to gather requirements, translating those requirements into functional solutions, and ensuring the quality and performance of the developed applications. Required Skills & Qualifications Education: A Bachelor's Degree is required. Experience: 6 years of experience in software development is expected. This level of experience indicates a proficiency in designing, developing, and implementing complex software solutions. Programming Languages: Demonstrated proficiency in Python is essential. Data Visualization & Business Intelligence: Expertise in Power BI for creating insightful reports and dashboards. Data Warehousing & Analytics: Experience with BigQuery for data analysis and querying. Artificial Intelligence: Familiarity with AI concepts and their application in business solutions. Power Platform Development: Strong skills in Power Apps for building custom applications, Power Automate for workflow automation, and Copilot Studio for creating intelligent chatbots. Microsoft Technologies: Proficiency in Microsoft Sharepoint for collaboration and document management, Microsoft Copilot for enhanced productivity, and AI Builder for incorporating AI capabilities into applications. Data Management: Experience with Microsoft Dataverse for data storage and management. API Integration: Ability to work with Microsoft Graph API and REST APIs for integrating with external systems. Cloud Computing: Solid understanding of Azure Services and GCP for cloud-based application deployment and management. Integration Technologies: Experience with Logic Apps and Azure Functions for building integrations and automating tasks. Data Management & Integration: Ability to perform Data Integration and Migration of data. Software Development Best Practices: Strong understanding of Reporting , Analytics , Testing , Quality Assurance , and UAT methodologies. Collaboration & Communication: Excellent Collaboration and Support skills for working effectively with cross-functional teams. Application Lifecycle Management: Experience in App Development , Modernization , and Optimization of existing applications. Workflow Automation: Ability to design and implement Workflow Automation solutions. What We Offer

Software Engineer (3) - Core Engineer 0

RLE India Private Limited•

Chennai

•full time

Job Summary We are seeking a highly motivated and skilled Software Engineer to join our core engineering team. This role will be responsible for developing and maintaining core software components, leveraging a variety of technologies to deliver high-quality solutions. The ideal candidate will possess a strong foundation in software development principles and a passion for continuous learning. Key Responsibilities This role will focus on the development and maintenance of core software components, ensuring their reliability, scalability, and performance. Specific responsibilities will be defined based on project needs and evolving business requirements. Required Skills & Qualifications Education: A Bachelor's Degree is required. Programming Languages: Proficiency in Python is essential. Data Analytics & Business Intelligence: Experience with Power BI for data visualization and reporting, and BigQuery for data warehousing and analysis. Artificial Intelligence & Machine Learning: Familiarity with AI concepts and applications, including experience with Microsoft Copilot , Copilot Studio , and AI Builder . Microsoft Power Platform: Strong skills in Power Apps for low-code application development and Power Automate for Workflow Automation . Cloud Computing: Experience with GCP and Azure Services , including Azure Functions and Logic Apps . Data Management: Knowledge of Dataverse for data storage and management. API Integration: Ability to work with REST APIs and Microsoft Graph API for data integration and application connectivity. User Interface & Experience: Understanding of User Experience ( UX ) and UI design principles. Software Development Lifecycle: Experience with Testing , Quality Assurance , and UAT processes to ensure software quality. Collaboration & Communication: Excellent Collaboration and Support skills to work effectively within a team environment. Microsoft Ecosystem: Proficiency with Microsoft Sharepoint . Experience: 6 years of experience are required. This indicates a senior level of experience, with expectations of independent problem-solving, mentorship of junior team members, and contribution to architectural decisions. Work Mode: onsite

Software Engineer

RLE India Private Limited•

Chennai

•full time

Job Summary We are seeking a skilled and motivated Software Engineer to join our dynamic team. This role will be based onsite and offers an exciting opportunity to contribute to innovative projects within the IT / Technology industry. Key Responsibilities The Software Engineer will be responsible for designing, developing, and implementing software solutions. This includes working with various technologies and methodologies to ensure high-quality, scalable, and secure applications. Required Skills & Qualifications Education: A Bachelor's Degree is required. Experience: 1 - 5 years of experience in software development is expected. This level of experience suggests a blend of foundational knowledge and practical application, with the ability to work independently and contribute to team goals. Pega: Demonstrated proficiency in Pega , including Pega PRPC Proficiency and Pega RPA Service . This encompasses a strong understanding of the Pega platform and its capabilities. Programming Languages: Expertise in programming languages such as Python , JavaScript , and C# . .NET Development: Experience as a .NET Developer , including working with .Net Framework and developing Customized .Net Components . RPA: Familiarity with RPA (Robotic Process Automation) principles and tools. GenAI: Understanding of GenAI (Generative Artificial Intelligence) concepts and applications. Cloud Computing: Experience with Google Cloud Platform . AIPGEE: Knowledge of AIPGEE . Software Development Methodologies: Proficiency in Test-driven development , Continuous integration , and Continuous delivery . Security Practices: Strong understanding of Encryption , Anonymization , and general Security best practices. Pega Specific Skills: Competency in Adaptors , Interrogation , Match Rules , Package Server , and the Synchronization Engine . Other Technologies: Experience with OCR (Optical Character Recognition) and Building Automation . Software Engineering Fundamentals: Solid foundation in Functions , Authentication , and Exception Handling . Deployment: Understanding of the Deployment Process .

Chassis Design Release Engineer / Tire specialist

RLE India Private Limited•

Chennai

•full time

Job Summary We are seeking a highly skilled and experienced Chassis Design Release Engineer with a specialization in tire technology to join our team. This role will be responsible for overseeing the release and validation of chassis components, with a particular focus on tire design, development, and testing. The ideal candidate will possess a strong analytical background and a proven ability to solve complex engineering problems within the automotive industry. Key Responsibilities This role will involve a range of responsibilities related to chassis design release and tire expertise, including: Overseeing the release of chassis components, ensuring adherence to quality standards and engineering best practices. Providing specialized expertise in tire design, development, and testing, contributing to the overall performance and safety of our vehicles. Conducting thorough Root Cause Analysis to identify and resolve issues related to chassis components and tire performance. Leading DFMEA (Design Failure Mode and Effects Analysis) and PFMEA (Process Failure Mode and Effects Analysis) activities to proactively identify and mitigate potential risks. Developing and implementing robust Control Plans to ensure consistent quality and performance throughout the manufacturing process. Managing PPAP (Production Part Approval Process) submissions, ensuring that all requirements are met before production release. Required Skills & Qualifications To be successful in this role, candidates must possess the following skills and qualifications: Educational Background: A Bachelor’s/ Master’s Degree in Engineering, specifically in Mechanical or Automobile Engineering. Experience: A minimum of 6 - 8 years of experience in a related engineering role within the automotive industry, demonstrating a strong understanding of chassis design and release processes. This level of experience indicates a seasoned professional capable of independent work and mentorship. Analytical Skills: Demonstrated ability to analyze complex data and draw meaningful conclusions, supporting data-driven decision-making. Problem-Solving Skills: Proven ability to identify, analyze, and resolve engineering problems effectively and efficiently. Communication Skills: Excellent written and verbal communication skills, with the ability to clearly and concisely communicate technical information to both technical and non-technical audiences. Tire Expertise: Deep understanding of Tire Design , Tire Development , and Tire Testing methodologies. Industry Standards: Familiarity with industry standards and regulations, including ETRTO , T&RA , and SAE . Tire Process Knowledge: Comprehensive knowledge of the Tire Building Process and Wheel Development Process . Engineering Methodologies: Proficiency in DFSS (Design for Six Sigma), Shainin , and DOE (Design of Experiments). Software Proficiency: Strong working knowledge of UG/NX , Catia V5 , and PLM (Product Lifecycle Management) systems, including Team Center . Performance Analysis: Expertise in Fatigue , NVH (Noise, Vibration, and Harshness), and Handling characteristics. Material Science: Understanding of Stiffness and material properties related to vehicle performance. Manufacturing Process: Familiarity with Vehicle Assembly Process , Casting , Sheet Metal , and Forging processes. Simulation: Experience with Simulation tools for analyzing vehicle performance. Vehicle Dynamics: Solid understanding of Vehicle Dynamics principles. Quality Assurance: Knowledge of PPA (Product and Process Audit) methodologies. What We Offer Salary: