Python Fullstack Developer with Gen AI

Position Overview: The AI CoE team is seeking Gen AI Fullstack Software Engineers to work on the AI ecosystem. The GenAI Fullstack Engineer will be responsible for designing, implementing, and deploying scalable and efficient AI solutions with a focus on privacy, security, and fairness. Key components include Angular and React JS based user interfaces, a robust set of Application Programming Interfaces (APIs) enabling a wide range of platform integration capabilities, a flexible Machine Learning (ML) and document processing pipeline. This role will work directly with business partners and other IT team members to understand desired system requirements and to deliver effective solutions within the Agile methodology and participate in all phases of the development and system support life cycle. Primary responsibilities are to build an AI Platform(s) leveraging the LLMs and other Gen AI Capabilities and provide design solution for portal integrations, enhancement, and automation requests. The ideal candidate is a technologist that brings a fresh perspective and passion to solve complex functional and technical challenges in a fast-paced and team-oriented environment. Job Responsibilities: • Full stack development including triage, design, coding and implementation. • Build enterprise grade AI solutions with focus on privacy, security, fairness. • Perform code reviews with scrum teams to approve for Production deployment. • Conduct research to identify new solutions and methods to fulfill diverse and evolving business needs • Establish/Improve/Maintain Proactive monitoring and management of supported assets assuring performance, availability, security, and capacity • Maintains a strong and collaborative relationship with delivery partners and business stakeholders. Qualifications: Education: • Degree in Computer Science, Artificial Intelligence, or a related field. Experience: • Minimum of 8-11 years of experience in Workforce Management. Skills: • This position requires a highly technical, hands-on, motivated and collaborative individual with exceptional communication skills, proven experience working with diverse teams of technical architects, business users and IT areas on all phases of the software development life-cycle • 8+ years of total experience. • 3+ years of experience in Fullstack development (Frontend, Backend and Cloud) • 2+ years experience in DevOps. • 2+ year in developing Gen AI Solutions and its integration with other systems. Detailed list of Skillset required – • ### Front-End Development Skills • 1. HTML/CSS/JavaScript: Proficiency in the core technologies for building web interfaces. • 2. Front-End Frameworks: React • 3. UI/UX Design: Basic understanding of user experience and user interface design principles. • • ### Back-End Development Skills • 1. Server-Side Languages: Proficiency in server-side languages such as Python, Node.js. • 2. APIs: Experience in building and consuming RESTful, Flask / Fast API / and GraphQL APIs. • 3. Database Management: Knowledge of SQL and NoSQL databases, including MySQL, PostgreSQL, MongoDB, etc. • • ### DevOps and Cloud Skills • 1. Containerization and Orchestration: Experience with Docker and Kubernetes / OpenShift for containerization and orchestration of applications. • 2. CI/CD Pipelines: Knowledge of continuous integration and continuous deployment tools and practices using GitHub Actions • 3. Security Best Practices: understanding of security principles and best practices for protecting data and systems, including IAM, encryption and network Security. • 4. Cloud Services: Familiarity with cloud platforms like AWS for deploying and managing applications and AI models. • • ### AI and Machine Learning Skills • 1. Foundations in Machine Learning and Deep Learning: Understanding algorithms, neural networks, supervised and unsupervised learning, and deep learning frameworks like TensorFlow, PyTorch, and Keras. • 2. Generative Models: Knowledge of generative models such as GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and Transformers. • 3. Natural Language Processing (NLP): Knowledge in NLP techniques and libraries (e.g., spaCy, NLTK, Hugging Face Transformers) for text generation tasks. • 4. Model Deployment: Experience with deploying models using services like TensorFlow Serving, TorchServe, or cloud-based solutions (e.g., AWS SageMaker, Google AI Platform). • 5. Understanding of implementing Prompt Engineering, Finetuning and RAG…