Responsibilities • Provides senior level system analysis, design, development, and implementation of applications and databases. Integrates third party products. • Translates technical specifications into code for complex new or enhancement projects for internal clients. Writes programs, develops code, tests artifacts, and produces reports. Employs software development techniques to ensure tests are implemented in a way that supports automation. • Elevates code into the development, test, and production environments on schedule. Provides follow up production support. Submits change control requests and documents. • Thoroughly understands software development methodology. Thoroughly understands development architecture standards. • Trains and mentors’ staff with less experience. Resolves elevated issues. • Participates in design, code, and test inspections throughout the life cycle to identify issues. Explains technical considerations at related meetings, including those with internal clients. Performs systems analysis activities. • Interfaces with cross functional team members and communicates systems issues at the appropriate technical level for each audience. • Thoroughly understands and complies with Information Technology and Information Security policies and procedures and verifies that deliverables meet requirements. • Qualification: 10+ years of industry experience • Hands-on knowledge of AWS services, with experience and awareness of features such as Lambda, DynamoDB, S3, Glue, IAM, CloudFormation, and other AWS services. • Strong proficiency in Python coding and development skills, including unit testing and end-to-end testing. • Proficient in JavaScript and React UI development. • Experience in API development. Role Overview: The role centers on AWS and Python development, with a strong back-end focus. While some front-end work in React is expected, it is secondary. The position also includes exposure to AI/ML technologies, supporting the build of an internal virtual advisor platform (similar to a ChatGPT-style copilot for financial queries). Ideal Candidate Profile: • Strong AWS and Python development experience • Familiarity with AI/ML lifecycle (data prep, training, deployment, monitoring) • - Model Development Lifecycle stages: Data Preparation, Training, Evaluation, Hosting and Monitoring - AI/ML Concepts: Supervised learning, unsupervised learning, deep learning, and model evaluation techniques • - Model Development Lifecycle stages: Data Preparation, Training, Evaluation, Hosting and Monitoring - AI/ML Concepts: Supervised learning, unsupervised learning, deep learning, and model evaluation techniques • React UI experience (lighter need) • AWS Machine Learning Specialty certification – nice-to-have • SageMaker knowledge – nice-to-have, not core