What You'll Do As a Senior AI Engineer, you will design, develop, deploy, and scale enterprise-grade AI and Machine Learning solutions that drive intelligent automation and business transformation. • Design and develop end-to-end AI/ML solutions for real-world business problems. • Build predictive models, classification systems, recommendation engines, and intelligent automation solutions. • Apply supervised, unsupervised, and deep learning techniques based on business requirements. • Develop and optimize data pipelines, feature engineering, and model training workflows. • Evaluate and improve model accuracy, scalability, robustness, and business impact. • Build and deploy scalable model-serving APIs using Python, FastAPI, Flask, or similar frameworks. • Deploy AI solutions using Docker, microservices, CI/CD pipelines, and cloud-native architectures. • Monitor model performance, data quality, model drift, and retraining requirements. • Troubleshoot production issues across AI models, APIs, and data pipelines. • Apply MLOps practices for model versioning, deployment, monitoring, and lifecycle management. • Implement Responsible AI practices, including explainability, bias mitigation, governance, and security. • Collaborate with Data Scientists, Data Engineers, Software Engineers, Product Managers, and business stakeholders. • Mentor junior engineers and contribute to architecture, code reviews, and technical best practices. • Stay current with emerging AI, Generative AI, LLM, and cloud technologies. What We Seek In You • 5–8 years of experience in AI Engineering, Machine Learning, Applied AI, or related fields. • Strong hands-on expertise in Python and SQL. • Machine Learning and Deep Learning • Supervised and Unsupervised Learning • Feature Engineering and Model Evaluation • Model Optimization and Validation • Hands-on experience with TensorFlow, PyTorch, Keras, Scikit-learn, NumPy, and Pandas. • Experience building and deploying production-grade AI/ML applications. • Strong experience with FastAPI, Flask, REST APIs, and Microservices. • Hands-on experience with Docker, Git, CI/CD, and cloud-native deployments. • Experience with at least one major cloud platform: Azure, AWS, or GCP. • Experience with AI/ML platforms such as Azure Machine Learning, AWS SageMaker, or Vertex AI. • Strong understanding of MLOps, model monitoring, model drift, and retraining workflows. • Excellent problem-solving, debugging, communication, and stakeholder management skills. • Ability to translate complex business challenges into scalable AI-powered solutions. Preferred Qualifications • Experience with Generative AI, Large Language Models (LLMs), RAG, and NLP. • Exposure to Computer Vision and advanced AI use cases. • Experience with MLOps tools such as MLflow, Kubeflow, or Apache Airflow. • Familiarity with Apache Spark and Big Data technologies. • Understanding of Responsible AI, Explainable AI (XAI), AI Governance, and AI Ethics. • Experience designing scalable, secure, and cloud-native AI architectures. • Experience in domains such as Manufacturing, Automotive, Supply Chain, Financial Services, Healthcare, or Enterprise Analytics. Life at Next At Next, we enable high-growth enterprises to transform their vision into reality through technology, data, and AI. We foster a culture of agility, innovation, continuous learning, and hands-on leadership. Perks of Working With Us • Clear career growth and accelerated learning opportunities. • Exposure to customers, product leaders, and emerging technologies. • Continuous learning and upskilling through Nexversity. • Mentorship and opportunities to explore diverse technologies and functions. • Hybrid work model supporting work-life balance. • Comprehensive family health insurance. • A collaborative environment focused on innovation, ownership, and growth. Join our passionate team and tailor your growth with us!