Senior AI Engineer

We are seeking an experienced AI Engineer to spearhead the design, development, and implementation of AI-driven solutions across various projects. The role involves working with advanced algorithms, developing scalable AI models, and driving automation initiatives. In addition to creating AI solutions that automate test case generation from Business Requirement Documents (BRDs), the candidate will contribute to diverse AI projects, including NLP, predictive modelling, and decision-making systems. A strong understanding of AI algorithms and experience with cross-cloud solutions is essential for this role.

Responsibilities:

• Lead the development of AI/ML models and solutions tailored to business needs across multiple domains.
• Apply well-known algorithms (e.g., decision trees, neural networks, reinforcement learning, clustering, and NLP techniques) to various business problems.
• Develop solutions that analyze BRDs and generate detailed test scenarios/test cases, including edge cases and negative testing.
• Collaborate on AI-driven projects across different verticals, such as predictive analytics, optimization, fraud detection, and personalized recommendations.
• Extract functional and non-functional requirements from BRDs and apply insights to AI solutions and testing processes.
• Design and implement comprehensive testing strategies, including automated testing solutions.
• Develop and deploy AI solutions across multiple cloud platforms (AWS, GCP, Azure) as required.
• Work closely with stakeholders across teams to align AI solutions with project goals.
• Research and implement cutting-edge AI technologies and techniques to enhance the AI capabilities within the organization.
• Leverage test automation and other development tools to enhance workflows and optimize processes.
• Mentor junior engineers, lead AI development teams, and ensure best practices are followed.

Qualifications:

• Expertise in building AI models using frameworks like TensorFlow, PyTorch, AWS SageMaker, or similar tools.
• Deep understanding of well-known AI/ML algorithms such as Supervised and unsupervised leaning, deep learning, NLP algorithms and reinforcement learning.
• Experience in automating test case generation from BRDs and defining test strategies.
• Strong experience with AWS services (e.g., SageMaker, Lambda, S3) and cross-cloud environments
  
• Experience in ETL, data processing, and working with large datasets (e.g., structured/unstructured data).
• Experience with test automation tools like Selenium, TestNG, or similar.
• Proficiency with continuous integration/continuous deployment (CI/CD) and tools like Jenkins, Docker, Kubernetes