4 Genai Integration Jobs

Ready to build the future with AI At Genpact, we don&rsquot just keep up with technology&mdashwe set the pace. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos AI Gigafactory, our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to agentic AI, our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, innovation-driven environment, love building and deploying cutting-edge AI solutions, and want to push the boundaries of what&rsquos possible, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation, our teams implement data, technology, and AI to create tomorrow, today. Get to know us at genpact.com and on LinkedIn, X, YouTube, and Facebook. Inviting applications for the role of [Manager], [Technical Architect, Gen-AI]! This position is based in India (preferably NCR) and is aimed at individuals who can lead the design and technical direction of enterprise-grade AI/ML, analytics, and full-stack solutions. As a Technical Architect, you will play a crucial role in shaping system architecture, guiding engineering teams, and ensuring robust, scalable, and maintainable software solutions using modern cloud and application technologies. Responsibilities . Lead the technical architecture and design of end-to-end solutions across cloud and hybrid environments. . Translate complex business requirements into scalable, performant, and secure technical designs. . Collaborate closely with engineering, product, and business teams to align architectural goals with delivery objectives. . Provide technical leadership and mentorship to development teams across technologies including backend, frontend, DevOps, and data layers. . Define and enforce coding standards, design principles, architectural best practices, and governance processes. . Drive cloud-native design on Azure, incorporating services such as Azure App Services, Azure Functions, etc. . Actively contribute to POCs, reference architectures, reusable templates, and solution accelerators. . Stay updated with emerging tools, technologies, and frameworks to recommend improvements and modernize existing systems. Qualifications we seek in you! Minimum Qualifications . BE/B Tech/MCA or equivalent degree in technical discipline. . Excellent written and verbal communication skills, with the ability to articulate complex technical concepts clearly to varied audiences. Preferred Qualifications/ Skills . Hands-on experience in software development. . Strong expertise in designing and implementing solutions using Python. . Experience in AI/ML model deployment, MLOps, or GenAI integration. . Deep understanding of Azure cloud ecosystem. . Understanding of microservices architecture, API and integration patterns. . Familiarity with databases (SQL/NoSQL), messaging systems, caching, and distributed systems. . Strong problem-solving ability and experience with troubleshooting and performance optimization. . Knowledge/experience of FnA domain (R2R, S2P, O2C) is a strong plus. Why join Genpact . Lead AI-first transformation - Build and scale AI solutions that redefine industries . Make an impact - Drive change for global enterprises and solve business challenges that matter . Accelerate your career&mdashGain hands-on experience, world-class training, mentorship, and AI certifications to advance your skills . Grow with the best - Learn from top engineers, data scientists, and AI experts in a dynamic, fast-moving workplace . Committed to ethical AI - Work in an environment where governance, transparency, and security are at the core of everything we build . Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the 140,000+ coders, tech shapers, and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

Ready to build the future with AI At Genpact, we don&rsquot just keep up with technology&mdashwe set the pace. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos AI Gigafactory, our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to agentic AI, our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, innovation-driven environment, love building and deploying cutting-edge AI solutions, and want to push the boundaries of what&rsquos possible, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation, our teams implement data, technology, and AI to create tomorrow, today. Get to know us at genpact.com and on LinkedIn, X, YouTube, and Facebook. Inviting applications for the role of [Manager], [Technical Architect, Gen-AI]! This position is based in India (preferably NCR) and is aimed at individuals who can lead the design and technical direction of enterprise-grade AI/ML, analytics, and full-stack solutions. As a Technical Architect, you will play a crucial role in shaping system architecture, guiding engineering teams, and ensuring robust, scalable, and maintainable software solutions using modern cloud and application technologies. Responsibilities . Lead the technical architecture and design of end-to-end solutions across cloud and hybrid environments. . Translate complex business requirements into scalable, performant, and secure technical designs. . Collaborate closely with engineering, product, and business teams to align architectural goals with delivery objectives. . Provide technical leadership and mentorship to development teams across technologies including backend, frontend, DevOps, and data layers. . Define and enforce coding standards, design principles, architectural best practices, and governance processes. . Drive cloud-native design on Azure, incorporating services such as Azure App Services, Azure Functions, etc. . Actively contribute to POCs, reference architectures, reusable templates, and solution accelerators. . Stay updated with emerging tools, technologies, and frameworks to recommend improvements and modernize existing systems. Qualifications we seek in you! Minimum Qualifications . BE/B Tech/MCA or equivalent degree in technical discipline. . Excellent written and verbal communication skills, with the ability to articulate complex technical concepts clearly to varied audiences. Preferred Qualifications/ Skills . Hands-on experience in software development. . Strong expertise in designing and implementing solutions using Python. . Experience in AI/ML model deployment, MLOps, or GenAI integration. . Deep understanding of Azure cloud ecosystem. . Understanding of microservices architecture, API and integration patterns. . Familiarity with databases (SQL/NoSQL), messaging systems, caching, and distributed systems. . Strong problem-solving ability and experience with troubleshooting and performance optimization. . Knowledge/experience of FnA domain (R2R, S2P, O2C) is a strong plus. Why join Genpact . Lead AI-first transformation - Build and scale AI solutions that redefine industries . Make an impact - Drive change for global enterprises and solve business challenges that matter . Accelerate your career&mdashGain hands-on experience, world-class training, mentorship, and AI certifications to advance your skills . Grow with the best - Learn from top engineers, data scientists, and AI experts in a dynamic, fast-moving workplace . Committed to ethical AI - Work in an environment where governance, transparency, and security are at the core of everything we build . Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the 140,000+ coders, tech shapers, and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

AI Model Deployment & Integration: Deploy and manage AI/ML models, including traditional machine learning and GenAI solutions (e.g., LLMs, RAG systems). Implement automated CI/CD pipelines for seamless deployment and scaling of AI models. Ensure efficient model integration into existing enterprise applications and workflows in collaboration with AI Engineers. Optimize AI infrastructure for performance and cost efficiency in cloud environments (AWS, Azure, GCP). Monitoring & Performance Management: Develop and implement monitoring solutions to track model performance, latency, drift, and cost metrics. Set up alerts and automated workflows to manage performance degradation and retraining triggers. Ensure responsible AI by monitoring for issues such as bias, hallucinations, and security vulnerabilities in GenAI outputs. Collaborate with Data Scientists to establish feedback loops for continuous model improvement. Automation & MLOps Best Practices: Establish scalable MLOps practices to support the continuous deployment and maintenance of AI models. Automate model retraining, versioning, and rollback strategies to ensure reliability and compliance. Utilize infrastructure-as-code (Terraform, CloudFormation) to manage AI pipelines. Security & Compliance: Implement security measures to prevent prompt injections, data leakage, and unauthorized model access. Work closely with compliance teams to ensure AI solutions adhere to privacy and regulatory standards (HIPAA, GDPR). Regularly audit AI pipelines for ethical AI practices and data governance. Collaboration & Process Improvement: Work closely with AI Engineers, Product Managers, and IT teams to align AI operational processes with business needs. Contribute to the development of AI Ops documentation, playbooks, and best practices. Continuously evaluate emerging GenAI operational tools and processes to drive innovation. Qualifications & Skills: Education: Bachelor's or Master's degree in Computer Science, Data Engineering, AI, or a related field. Relevant certifications in cloud platforms (AWS, Azure, GCP) or MLOps frameworks are a plus. Experience: 3+ years of experience in AI/ML operations, MLOps, or DevOps for AI-driven solutions. Hands-on experience deploying and managing AI models, including LLMs and GenAI solutions, in production environments. Experience working with cloud AI platforms such as Azure AI, AWS SageMaker, or Google Vertex AI. Technical Skills: Proficiency in MLOps tools and frameworks such as MLflow, Kubeflow, or Airflow. Hands-on experience with monitoring tools (Prometheus, Grafana, ELK Stack) for AI performance tracking. Experience with containerization and orchestration tools (Docker, Kubernetes) to support AI workloads. Familiarity with automation scripting using Python, Bash, or PowerShell. Understanding of GenAI-specific operational challenges such as response monitoring, token management, and prompt optimization. Knowledge of CI/CD pipelines (Jenkins, GitHub Actions) for AI model deployment. Strong understanding of AI security principles, including data privacy and governance considerations.

Key Responsibilities AI Model Deployment & Integration: Deploy and manage AI/ML models, including traditional machine learning and GenAI solutions (e.g., LLMs, RAG systems). Implement automated CI/CD pipelines for seamless deployment and scaling of AI models. Ensure efficient model integration into existing enterprise applications and workflows in collaboration with AI Engineers. Optimize AI infrastructure for performance and cost efficiency in cloud environments (AWS, Azure, GCP). Monitoring & Performance Management: Develop and implement monitoring solutions to track model performance, latency, drift, and cost metrics. Set up alerts and automated workflows to manage performance degradation and retraining triggers. Ensure responsible AI by monitoring for issues such as bias, hallucinations, and security vulnerabilities in GenAI outputs. Collaborate with Data Scientists to establish feedback loops for continuous model improvement. Automation & MLOps Best Practices: Establish scalable MLOps practices to support the continuous deployment and maintenance of AI models. Automate model retraining, versioning, and rollback strategies to ensure reliability and compliance. Utilize infrastructure-as-code (Terraform, CloudFormation) to manage AI pipelines. Security & Compliance: Implement security measures to prevent prompt injections, data leakage, and unauthorized model access. Work closely with compliance teams to ensure AI solutions adhere to privacy and regulatory standards (HIPAA, GDPR). Regularly audit AI pipelines for ethical AI practices and data governance. Collaboration & Process Improvement: Work closely with AI Engineers, Product Managers, and IT teams to align AI operational processes with business needs. Contribute to the development of AI Ops documentation, playbooks, and best practices. Continuously evaluate emerging GenAI operational tools and processes to drive innovation. Qualifications & Skills Education: Bachelors or Masters degree in Computer Science, Data Engineering, AI, or a related field. Relevant certifications in cloud platforms (AWS, Azure, GCP) or MLOps frameworks are a plus. Experience: 3+ years of experience in AI/ML operations, MLOps, or DevOps for AI-driven solutions. Hands-on experience deploying and managing AI models, including LLMs and GenAI solutions, in production environments. Experience working with cloud AI platforms such as Azure AI, AWS SageMaker, or Google Vertex AI. Technical Skills: Proficiency in MLOps tools and frameworks such as MLflow, Kubeflow, or Airflow. Hands-on experience with monitoring tools (Prometheus, Grafana, ELK Stack) for AI performance tracking. Experience with containerization and orchestration tools (Docker, Kubernetes) to support AI workloads. Familiarity with automation scripting using Python, Bash, or PowerShell. Understanding of GenAI-specific operational challenges such as response monitoring, token management, and prompt optimization. Knowledge of CI/CD pipelines (Jenkins, GitHub Actions) for AI model deployment. Strong understanding of AI security principles, including data privacy and governance considerations.