Software Engineer III - Agentic AI Developer
- Develops and implements GenAI and Agentic AI solutions using Python to enhance automation and decision-making processes.
- Collaborates with cross-functional teams to integrate AI technologies into existing systems, leveraging Python for robust solutions
- Analyzes and interprets complex data sets using Python to support AI-driven insights and recommendations.
- Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
- Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
- Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
- Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
- Contributes to software engineering communities of practice and events that explore new and emerging technologies
- Collaborate with high-performing teams and individuals throughout the firm to accomplish common goals
- Formal training or certification on software engineering concepts and 3+ years applied experience
- Expertise in application, data and infrastructure architecture disciplines
- Design and build experience on large enterprise software solutions in public or private cloud environments.
- Experience with Python or Java, SpringBoot, ReactJS, Kafka, AWS Lamda/ECS/RDS, workflow design and rules systems experience with BPM toolsets (Camunda).
- Hands-on practical experience in system design, application development, testing, and operational stability
- Proficient in coding in one or more languages
- Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
- Overall knowledge of the Software Development Life Cycle
- Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
- Experience with modern front-end technologies
- Experience to cloud technologies
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