Software Engineering Lead Analyst T500-13268

Role Title: Full Stack Engineer

Title: Software Engineering Lead Analyst

Position Summary:

The AI CoE team is seeking Fullstack Software Engineers to work on the AI ecosystem. The 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 includes 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) document processing pipeline and integration with various Robotic Process Automation (RPA) platforms. 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 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 Description & Responsibilities:

Job Responsibilities:
 Full stack development including triage, design, coding and implementation
 Plan and implement procedures that will maximize operating efficiency for application integration technologies, this includes managing the evolution and maturity in agile delivery, automating and improving development operational processes and engineering (Dev Ops).
 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
 Identify and drive process improvement opportunities
 Maintains a strong and collaborative relationship with delivery partners and business stakeholders

Required Experience / Qualifications:
 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
 2-3 years of experience with Azure or AWS services and Devops practices and tools
 6+ years of total experience.
 5+ years of experience in FullStack development (Frontend, Backend and Cloud)
 1+ years experience in DevOps.
 1+ year in developing Gen AI Solutions and its integration with other systems.

Detailed list of Skillset required:

Front-End Development Skills:
 HTML/CSS/JavaScript: Proficiency in the core technologies for building web interfaces.
 Front-End Frameworks: Knowledge of frameworks like React, Angular, or Vue.js for creating interactive and responsive user interfaces.
 UI/UX Design: Basic understanding of user experience and user interface design principles.

Back-End Development Skills:
 Server-Side Languages: Proficiency in server-side languages such as Python, Node.js.
 APIs: Experience in building and consuming RESTful , Flask / Fast API / and GraphQL APIs.
 Database Management: Knowledge of SQL and NoSQL databases, including MySQL, PostgreSQL, MongoDB, etc.

DevOps and Cloud Skills:
 Containerization and Orchestration: Experience with Docker and Kubernetes / OpenShift for containerization and orchestration of applications.
 CI/CD Pipelines: Knowledge of continuous integration and continuous deployment tools and practices.
 Security Best Practices: understanding of security principles and best practices for protecting data and systems , including IAM , encryption and network Security.
 Cloud Services: Familiarity with cloud platforms like AWS, Google Cloud, or Azure for deploying and managing applications and AI models.

AI and Machine Learning Skills:
 Foundations in Machine Learning and Deep Learning: Understanding algorithms, neural networks, supervised and unsupervised learning, and deep learning frameworks like TensorFlow, PyTorch, and Keras.
 Generative Models: Knowledge of generative models such as GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and Transformers.
 Natural Language Processing (NLP): Knowledge in NLP techniques and libraries (e.g., spaCy, NLTK, Hugging Face Transformers) for text generation tasks.
 Model Deployment: Experience with deploying models using services like TensorFlow Serving, TorchServe, or cloud-based solutions (e.g., AWS SageMaker, Google AI Platform).
 Basic understanding of implementing Prompt Engineering, Finetuning and RAG.

Additional Skills:
 Version Control: Proficiency with Git and version control workflows.
 Software Development Practices: Understanding of agile methodologies, testing, and code review practices.

Education and Training Required:
 Degree in Computer Science, Artificial Intelligence, or a related field.,