About this role
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. Explore Life at Zensar and join us to Grow. Own. Achieve. Learn. to be the best version of yourself.
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. Role Overview We are seeking a skilled AI Engineer to design, develop, deploy, and optimize AI-powered solutions that drive business value. The ideal candidate will have expertise in Machine Learning, Generative AI, Large Language Models (LLMs), and MLOps, with experience building scalable AI applications in cloud environments.
Key Responsibilities
• Design, develop, and deploy AI/ML models and Generative AI solutions. • Build intelligent applications leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI frameworks. • Develop and optimize machine learning pipelines for training, evaluation, and deployment. • Implement data preprocessing, feature engineering, and model performance tuning. • Integrate AI solutions into enterprise applications through APIs and microservices. • Collaborate with Data Engineers, Product Managers, Architects, and business stakeholders to identify AI use cases. • Monitor model performance, accuracy, drift, and scalability in production environments. • Implement MLOps best practices for model versioning, deployment, and monitoring. • Ensure AI solutions comply with security, privacy, and responsible AI guidelines. • Stay current with emerging AI technologies and industry best practices. Required Skills & Qualifications
• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field. • 4+ years of experience in AI/ML development. • Strong programming skills in Python. • Hands-on experience with machine learning frameworks such as: • TensorFlow • PyTorch • Scikit-learn
• Experience with Generative AI, LLMs, and prompt engineering. • Knowledge of RAG, vector databases, embeddings, and semantic search. • Experience with REST APIs, microservices, and application integration. • Strong understanding of data structures, algorithms, and software engineering principles. • Experience working with SQL and NoSQL databases. • Familiarity with Agile development methodologies. Preferred Skills
• Experience with Azure OpenAI, Vertex AI, Google Gemini, Anthropic Claude, or OpenAI models. • Exposure to LangChain, LangGraph, LlamaIndex, CrewAI, or similar Agentic AI frameworks. • Experience with MLOps tools such as MLflow, Kubeflow, or Vertex AI Pipelines. • Knowledge of Docker, Kubernetes, and CI/CD pipelines. • Experience with cloud platforms such as GCP, Azure, or AWS.
Technical Skills AI & Machine Learning
• Machine Learning • Deep Learning • NLP • Computer Vision • Generative AI • Large Language Models (LLMs) • Prompt Engineering • Retrieval-Augmented Generation (RAG) Programming & Frameworks
• Python • TensorFlow • PyTorch • Scikit-learn • LangChain • LangGraph • LlamaIndex Cloud & MLOps
• Vertex AI / Azure AI Services / AWS SageMaker • MLflow • Docker • Kubernetes • GitHub Actions / Azure DevOps Databases
• PostgreSQL • MongoDB • BigQuery • Pinecone • Weaviate • ChromaDB Key Competencies
• AI Solution Design • Model Development & Optimization • Problem Solving • Innovation Mindset • Analytical Thinking • Stakeholder Management • Communication & Collaboration Nice to Have
• Google Professional Machine Learning Engineer, Azure AI Engineer, or AWS ML Certification. • Experience building enterprise-scale AI copilots and chatbots. • Exposure to Responsible AI, AI Governance, and Model Explainability. • Experience in Retail, E-commerce, Supply Chain, or Customer Analytics domains. Success Metrics
• Successful deployment of scalable AI solutions. • Improved model accuracy, performance, and reliability. • Reduced deployment time through MLOps automation. • Increased business value through AI-driven insights and automation. • High stakeholder satisfaction and adoption of AI solutions.