• Review, evaluate, and annotate AI-generated content across text, images, audio, and video • Perform quality checks to ensure accuracy, consistency, and compliance with project guidelines • Identify edge cases, inconsistencies, and opportunities for improvement • Contribute to the development of high-quality datasets used to train advanced AI models • Participate in calibration and quality alignment activities • Provide feedback to help improve workflows and annotation guidelines

• Review AI-generated responses for clarity, accuracy, correctness, relevance, and overall quality. • Annotate and label language content according to detailed project guidelines. • Generate or evaluate prompts based on assignment requirements. • Identify linguistic errors, dataset concerns, and structural inconsistencies. • Provide clear, structured feedback to support improvements in AI performance. • Communicate complex language requirements clearly to both linguistic and non-linguistic stakeholders. • Collaborate with QA Leads and clients to apply feedback and maintain quality standards. • Participate in required client-facing meetings with your camera on. • Submit daily work reports and consistently meet productivity and quality expectations.

Role Description - Define and own the enterprise automation and AI strategy, balancing UiPath for RPA and Azure-native AI for intelligent solutions. - Lead end-to-end delivery — discovery, architecture, build, evaluation, deployment, and hyper care. - Establish CoE governance: intake, prioritization, reusable accelerators, LLMOps, and ROI tracking. - Build, mentor, and scale a high-performing automation/AI team across geographies. - Architect and deliver enterprise RPA solutions using UiPath and Power platform. - Design attended, unattended, and hybrid bots with robust exception handling, reusable frameworks, and audit controls. - Manage Orchestrator infrastructure (queues, assets, credentials, tenants) and CI/CD for bots. - Drive adoption of Automations. - Design and deliver GenAI/LLM-based solutions for document extraction, classification, summarization, decisioning, and conversational interfaces. Company Description At Zensar, we’re “experience-led everything”. We are committed to conceptualizing, designing, engineering, marketing, and managing digital solutions and experiences for over 130 leading enterprises. We are a company driven by a bold purpose: Together, we shape experiences for better futures. Whether for our clients, our people, or the world around us, this belief powers everything we do. At the heart of our culture is ONE with Client - a set of four core values that reflect who we are and how we work: One Zensar, Nurturing, Empowering, and Client Focus. Part of the $4.8 billion RPG Group, we’re a community of 10,000+ innovators across 30+ global locations, including Milpitas, Seattle, Princeton, Cape Town, London, Zurich, Singapore, and Mexico City. We believe the best work happens when individuality is celebrated, growth is encouraged, and well-being is prioritized. We are an equal employment opportunity (EEO) and affirmative action employer, committed to creating an inclusive workplace. All qualified applicants will be considered without regard to race, creed, color, ancestry, religion, sex, national origin, citizenship, age, sexual orientation, gender identity, disability, marital status, family medical leave status, or protected veteran status.

• Build scalable platform enablement for AI governance, including self-service workflows, reusable templates, risk tiering, policy-driven controls, and practical guidance for teams. • Define governance for agentic AI use cases, including human oversight, access management, monitoring, auditability, and escalation paths. • Partner with data and AI engineers, IT compliance, and a wide range of business stakeholders to make governance practical, scalable, and embedded in daily ways of working. • Translate applicable laws, standards, and internal policies, including but not limited to the EU AI Act, into governance processes that teams can understand and apply with confidence. • Strengthen our AI risk management approach by helping stakeholders navigate complex decisions, identifying improvement opportunities, and using automation to streamline our audit trail further.