Governance 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:

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

Energy Management- Project Performance Engineer

RLE India Private Limited•

Pune

•full time

Key Responsibilities The responsibilities of this role will encompass a broad range of tasks related to vehicle performance and energy management, requiring a proactive and detail-oriented approach. Required Skills & Qualifications To be successful in this role, candidates must possess a strong foundation in automotive engineering principles and a proven ability to apply their skills to real-world challenges. The following skills and qualifications are essential: Education: A Bachelor’s/ master’s degree in the Mechanical or Automotive domain is required. Experience: 6 - 9 years of relevant experience are expected, demonstrating a senior level of expertise and the ability to lead and mentor others. Energy Management: Demonstrated expertise in energy management principles and their application to automotive systems. Vehicle Performance: A thorough understanding of vehicle performance characteristics and the ability to optimize performance through various engineering techniques. CO2 & Fuel Consumption: Knowledge of CO2 emissions and fuel consumption optimization strategies. Electric Range: Understanding of factors influencing electric range and methods for maximizing range in electric vehicles. Functional Synthesis: Ability to perform functional synthesis to integrate various vehicle systems effectively. Attribute Management: Experience in attribute management, ensuring vehicle attributes meet target specifications. Technical Scorecard: Proficiency in developing and utilizing technical scorecards to track progress and identify areas for improvement. DVP&R: Familiarity with the Design Verification and Planning (DVP&R) process. Homologation: Understanding of homologation requirements and procedures. Coast Down: Knowledge of coast-down testing and analysis. Emission Test Cycles: Experience with emission test cycles and their interpretation. Vehicle Simulation: Ability to utilize vehicle simulation tools for performance analysis and optimization. Powertrain: A strong understanding of powertrain systems and their impact on vehicle performance. Calibration: Experience in powertrain calibration techniques. Weights: Knowledge of vehicle weight management and its impact on performance. Benchmarking: Ability to conduct benchmarking studies to identify best practices and competitive advantages. Issue Tracking: Proficiency in issue tracking and resolution. Milestone Governance: Experience in milestone governance and project management. Management Reporting: Ability to prepare and present management reports. Microsoft Suite: Proficiency in Microsoft Suite , including PowerPoint , Excel (including Macros ), and Word . Power BI: Experience with Power BI for data visualization and analysis. AI Technology: Basic understanding of AI Technology and its potential applications in automotive engineering. Analytical Skills: Strong analytical skills with the ability to interpret data and draw meaningful conclusions. Problem-Solving Skills: Excellent problem-solving skills with a demonstrated ability to identify and resolve complex issues. Communication Skills: Exceptional communication skills, both written and verbal, with the ability to effectively communicate technical information to both technical and non-technical audiences. Leadership: Demonstrated leadership qualities with the ability to motivate and inspire others. Responsibility: A strong sense of responsibility and accountability. Networking: Ability to build and maintain strong professional networks. What We Offer We value our employees and offer a competitive compensation package. Salary:

Project Performance Engineer

RLE India Private Limited•

Pune

•full time

Job Summary We are seeking a highly motivated and experienced Project Performance Engineer to join our team within the Automotive industry. This role will focus on ensuring optimal vehicle performance and adherence to stringent environmental standards. The ideal candidate will possess a strong analytical background and a proven ability to manage complex projects. Key Responsibilities The Project Performance Engineer will be responsible for a range of tasks related to vehicle performance and project oversight. This includes, but is not limited to, monitoring project milestones, generating management reports, and ensuring the successful completion of vehicle testing and homologation processes. The role requires a proactive approach to identifying and resolving issues, as well as a commitment to maintaining accurate technical documentation. Required Skills & Qualifications Education: A Bachelor’s/master’s degree in the Mechanical or Automotive domain is required. Experience: 8 - 12 years of relevant experience in vehicle performance engineering or a related field is expected. This level of experience indicates a seasoned professional capable of independently managing complex tasks and mentoring junior team members. Energy Management: Demonstrated expertise in Energy Management principles, with a focus on optimizing vehicle efficiency. Vehicle Performance: A thorough understanding of Vehicle Performance characteristics and their impact on overall vehicle dynamics. CO2 & Fuel Consumption: Deep knowledge of CO2 emissions and Fuel Consumption reduction strategies. Electric Range: Experience in analyzing and optimizing Electric Range for electric and hybrid vehicles. Functional Synthesis: Ability to perform Functional Synthesis to ensure seamless integration of vehicle systems. Attribute Management: Proficiency in Attribute Management techniques to define and control vehicle characteristics. Technical Scorecard: Experience in developing and utilizing Technical Scorecard systems to track performance metrics. DVP&R: Familiarity with DVP&R (Design Verification and Planning and Release) processes. Homologation: Knowledge of Homologation requirements and procedures. Coast Down: Understanding of Coast Down testing methodologies. Emission Test Cycles: Experience with various Emission Test Cycles and their application. Vehicle Simulation: Ability to utilize Vehicle Simulation tools for performance analysis and optimization. Powertrain: Strong understanding of Powertrain systems and their impact on vehicle performance. Calibration: Experience in Calibration of vehicle systems to achieve optimal performance. Weights: Knowledge of the impact of Weights on vehicle performance and efficiency. Benchmarking: Ability to perform Benchmarking studies to identify best practices and competitive advantages. Issue Tracking: Proficiency in Issue Tracking systems to manage and resolve vehicle performance issues. Milestone Governance: Experience in Milestone Governance to ensure project timelines are met. Management Reporting: Ability to generate clear and concise Management Reporting on project performance. Software Proficiency: Strong proficiency in the Microsoft Suite , including PowerPoint , Excel (including Macros ), and Word . Data Visualization: Experience using Power BI for data visualization and analysis. AI Technology: Familiarity with AI Technology and its application to vehicle performance optimization. Analytical Skills: Exceptional Analytical Skills to interpret data and identify trends. Problem-Solving Skills: Demonstrated Problem-Solving Skills to address complex vehicle performance challenges. Communication Skills: Excellent Communication Skills to effectively convey technical information to both technical and non-technical audiences. Leadership: Ability to demonstrate Leadership qualities and guide project teams. Responsibility: A strong sense of Responsibility and ownership for project outcomes. Networking: Ability to build and maintain effective Networking relationships with stakeholders. What We Offer Salary:

Artificial Intelligence Senior Associate

RLE India Private Limited•

Chennai

•Full-time

Artificial Intelligence Senior Associate Job Summary We are seeking a highly motivated and skilled Artificial Intelligence Senior Associate to join our growing team in Chennai. This role offers an exciting opportunity to contribute to cutting-edge AI and ML initiatives within a dynamic Technology environment. Key Responsibilities The Artificial Intelligence Senior Associate will be responsible for a range of tasks related to the development, deployment, and maintenance of AI and ML models and systems. This includes collaborating with cross-functional teams to define project requirements, designing and implementing solutions, and ensuring the quality and reliability of deployed models. Required Skills & Qualifications AI/ML : A strong understanding of artificial intelligence and machine learning principles, including various algorithms, techniques, and their practical applications. GCP : Proficiency in utilizing Google Cloud Platform ( GCP ) for developing and deploying AI and ML solutions. This includes experience with GCP services such as Vertex AI, BigQuery, and Cloud Storage. GenAI : Experience with Generative AI models and techniques, including understanding of large language models and their applications. AI Agents : Familiarity with the principles and implementation of AI Agents , including their design, development, and integration into existing systems. MLOps : Knowledge of MLOps practices and tools for automating and streamlining the machine learning lifecycle, from model development to deployment and monitoring. RESTful APIs : Ability to design and implement RESTful APIs for integrating AI and ML models with other systems and applications. Microservices : Experience with microservices architecture and its application in building scalable and resilient AI and ML systems. Data Pipelines : Ability to design and implement robust and efficient data pipelines for ingesting, transforming, and preparing data for AI and ML models. Model Monitoring : Experience with model monitoring techniques and tools for tracking model performance and identifying potential issues. Model Governance : Understanding of model governance principles and best practices for ensuring the ethical and responsible use of AI and ML models. Serverless : Familiarity with serverless computing concepts and technologies for building scalable and cost-effective AI and ML applications. Containerized : Experience with containerized deployments using technologies like Docker and Kubernetes . Agile : Experience working in an Agile development environment, with a focus on iterative development and continuous improvement. Product Management : Ability to collaborate with product management teams to define requirements and translate them into technical solutions. Reasoning : Strong analytical and reasoning skills for problem-solving and decision-making in complex situations. Tool-use : Ability to effectively utilize various AI and ML tools and technologies. APIs : Understanding of APIs and their role in integrating AI and ML models with other systems. Qualifications : A Bachelor's Degree is required. Experience Required : 3 - 5 years of relevant experience in the field of AI and ML . What We Offer We offer a competitive compensation package.

Software Engineer

RLE India Private Limited•

Chennai

•full time

Job Summary We are seeking two experienced Software Engineers to join our team in Bangalore. This role offers an opportunity to contribute to innovative projects within the IT / Technology industry. Key Responsibilities The specifics of key responsibilities were not provided. This section will be populated with responsibilities as they become available. Required Skills & Qualifications The ideal candidate will possess a strong foundation in software engineering principles and a proven ability to apply them to complex challenges. The following skills and qualifications are essential: SaaS : Demonstrated experience with Software as a Service (SaaS) platforms and architectures. MDM : Familiarity with Mobile Device Management (MDM) principles and technologies. Java : Proficiency in Java programming language, including object-oriented design and implementation. Informatica : Experience with Informatica for data integration and transformation. CDI : Understanding of Customer Data Integration ( CDI ) concepts and methodologies. CAI : Knowledge of Customer Analytics and Intelligence ( CAI ) tools and techniques. CDQ : Experience with CDQ for data quality management and improvement. CLAIRE : Familiarity with CLAIRE , a data science platform. API : Strong understanding of API design and development principles. REST : Proficiency in building and consuming REST ful APIs. Business Entity Modeling : Ability to create and maintain accurate Business Entity Models . Cost-Optimized Design : Experience in designing solutions with a focus on cost optimization. AI-Powered Match & Merge : Knowledge of AI -powered data matching and merging techniques. Ingestion : Experience with data ingestion processes and technologies. Integration : Proven ability to integrate disparate systems and data sources. Data Quality : Strong understanding of Data Quality principles and best practices. Legacy Mapping : Ability to map and understand Legacy systems and data structures. Workflow : Experience in designing and implementing Workflow solutions. Governance : Understanding of data Governance principles and practices. API Management : Experience with API Management platforms and tools. Encryption : Knowledge of data Encryption techniques and best practices. Anonymization : Experience with data Anonymization techniques. Analytical Skills : Strong analytical and problem-solving skills. Problem-Solving Skills : Demonstrated ability to identify and resolve complex technical issues. Communication Skills : Excellent written and verbal Communication Skills . Qualifications: A Bachelor's Degree is required. Experience Required: 10 - 10 years of relevant experience are expected, indicating a senior level of expertise and a proven track record in software engineering. What We Offer Salary: The salary details were not provided.

Artificial Intelligence Senior Associate

RLE India Private Limited•

Chennai

•full time

Job Summary We are seeking a highly motivated and skilled Artificial Intelligence Senior Associate to join our growing team. This role will focus on leveraging cutting-edge AI/ML techniques to solve complex business challenges within the IT / Technology industry. Key Responsibilities The Artificial Intelligence Senior Associate will be responsible for a range of tasks related to the development, deployment, and maintenance of AI/ML models and systems. This includes contributing to the full lifecycle of AI projects, from initial conception and design to implementation, testing, and ongoing monitoring. Required Skills & Qualifications AI/ML : A strong understanding of artificial intelligence and machine learning principles, including various algorithms and techniques for data analysis, prediction, and automation. GCP : Proficiency in utilizing Google Cloud Platform (GCP) for developing and deploying AI/ML solutions. This includes familiarity with GCP Services and their integration within a cloud-based environment. GenAI : Experience with Generative AI models and their applications. AI Agents : Knowledge of AI Agents and their implementation. RESTful APIs : Ability to design and integrate with RESTful APIs for seamless data exchange and system interoperability. Microservices : Understanding of Microservices architecture and its application in building scalable and resilient AI systems. MLOps : Experience with MLOps practices to streamline the machine learning lifecycle, including automation, continuous integration, and continuous delivery. Serverless : Familiarity with Serverless computing concepts and their application in building efficient and cost-effective AI solutions. Containerized : Experience with Containerized environments, such as Docker and Kubernetes , for deploying and managing AI applications. Agile : Proven ability to work within an Agile development framework, collaborating effectively with cross-functional teams. Product Management : Understanding of Product Management principles and their application in defining and delivering successful AI -powered products. Reasoning : Ability to apply logical Reasoning to solve complex problems and make informed decisions. Tool-use : Proficiency in utilizing various AI and ML tools and frameworks. APIs : Experience with APIs and their integration. Data Pipelines : Ability to design and implement robust Data Pipelines for efficient data processing and transformation. Model Training : Expertise in Model Training techniques and best practices. Model Deployment : Experience with Model Deployment strategies and tools. Model Versioning : Ability to implement Model Versioning to track and manage different versions of AI models. Model Monitoring : Proficiency in Model Monitoring techniques to ensure the ongoing performance and accuracy of AI models. Model Governance : Understanding of Model Governance principles and their application in ensuring responsible and ethical use of AI . Qualifications : A Bachelor's Degree is required. Experience Required : 3 - 5 years of relevant experience in the field of AI/ML is expected. This level of experience indicates a solid foundation in AI principles and a proven ability to contribute effectively to real-world projects. 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: