Software Developer

As a versatile and experienced Software Engineer, you will utilize your strong programming skills in C++, Java, Python, and JavaScript/TypeScript, along with a foundational understanding of machine learning (ML) and natural language processing (NLP). Your passion for software development, data science, and AI-driven applications will drive you to contribute to building scalable, intelligent, and user-friendly web applications. You will design, develop, and maintain web applications using JavaScript, TypeScript, and Python. Additionally, you will build and optimize backend services and APIs using Java, C++, or Python while applying multi-paradigm programming principles to solve complex engineering problems. Collaboration with data scientists to integrate ML/NLP models into production systems will be a key aspect of your role. In this position, you will conduct data analysis, data processing, and performance tuning for AI-driven features. Your involvement in the full software development life cycle (SDLC), including design, development, testing, and deployment, will be crucial. Staying updated with emerging technologies in AI, agentic systems, and web development will also be expected from you. To be successful in this role, you should hold a Bachelors or Masters degree in Computer Science, Information Technology, or a related field, along with 6-9 years of experience in software development with a focus on AI, data science, or web applications. Proficiency in programming languages such as C++, Java, Python, JavaScript, and TypeScript, as well as web development skills including HTML, CSS, and modern JS frameworks (React, Angular, etc.), is required. Knowledge of ML algorithms, NLP concepts, and data analysis is essential, and familiarity with Meta Language (Standard ML) or other functional programming paradigms would be a plus. A strong understanding of software engineering principles, version control, and agile methodologies is necessary. Preferred qualifications for this role include experience with agentic AI systems or AI research, exposure to cloud platforms (AWS, GCP, Azure) and DevOps practices, as well as contributions to open-source projects or research publications in AI/ML.,