Job Responsibilities
- Design, develop, and troubleshoot software solutions for complex business challenges
- Write secure, high-quality production code and review code from team members
- Identify and automate remediation of recurring issues to improve system stability
- Lead architectural design sessions and provide technical guidance for on-premises and cloud systems
- Promote adoption of new technologies through internal communities of practice
- Foster a culture of diversity, equity, and respect within the team
- Develop and maintain applications using Python and AWS
- Create and review architecture and design deliverables, ensuring best practices are followed
- Integrate AI/ML solutions into domain-specific operations processing systems
- Lead code reviews, design discussions, and agile planning sessions
- Collaborate with Site Reliability Engineering and monitoring teams to ensure system reliability and performance
Required Skills
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Strong experience building and running applications on AWS or other public cloud platforms
- Advanced proficiency in Python programming
- Proven experience in system design, application development, testing, and maintaining operational stability
- Skilled in automation, continuous delivery, and the full Software Development Life Cycle
- Experience with data processing pipelines and Directed Acyclic Graphs (DAGs) for machine learning or data workflows
- Demonstrated expertise in cloud, artificial intelligence, and machine learning technologies
- Understanding of IT systems in the financial services industry
- Experience with code reviews and agile methodologies
- Ability to communicate technical concepts clearly to both technical and non-technical stakeholders
- Commitment to continuous learning and creative problem-solving
Preferred Skills
- Experience with Cloud services, Infrastructure as Code (e.g., Terraform), and containerized application development
- Familiarity with data storage systems such as Postgres and OpenSearch, and AWS services including S3, SageMaker, and Bedrock
- Practical experience with Kubernetes, EKS, Docker, Kafka, MLOps, Large Language Model Operations (LLMOps), and event-driven systems
- Knowledge of security best practices in cloud and application development
- Experience integrating AI/ML models into production environments
- Ability to mentor and guide junior engineers
- Participation in technology events or software engineering communities