The Backend Engineer will design and maintain scalable backend systems, develop Python libraries, build APIs, and integrate AI models. Responsibilities include system automation, performance monitoring, and contributing to open-source projects.

The AWS DevOps Engineer will design, implement, and manage AWS infrastructure, support migrations, and utilize DevOps practices including CI/CD pipelines, Kubernetes, and Docker.

The AI/ML Solutions Architect will engage with customers to design scalable AI/ML architectures, ensuring best practices while collaborating with AWS and internal teams.

The Data Scientist collaborates on Applied AI projects, develops tools for Generative AI, and works on deep neural networks and simulations.

The ML Engineer will productionize machine learning models, enforce engineering standards, collaborate with Data Scientists and Engineers, and mentor junior staff.

The AWS DevOps Engineer will design and manage AWS infrastructure, drive migration projects, implement DevOps practices, and mentor junior team members.

The Full Stack Engineer will design, develop, and maintain scalable web applications using Python and React. Responsibilities include backend API development, database management, and creating responsive UIs. Collaboration with remote teams in an Agile/Scrum environment is essential.

The AI/ML Solutions Architect will design and implement scalable AI/ML architectures, manage relationships with customers, and create technical content while advocating for best practices in AI/ML solutions.

As an AWS Cloud Architect, you'll lead customer projects focusing on migration, DevOps, and solution design, while mentoring team members and resolving technical issues.

Manage the entire project lifecycle for cloud solutions, ensuring customer satisfaction, project delivery on time and within budget, and effective communication throughout.

The Account Manager will drive AWS business growth by building relationships, managing client accounts, and collaborating with sales and technical teams to deliver cloud solutions.

Manage customer communication and project lifecycle for AWS professional services, ensuring budget and timeline adherence while driving team delivery and stakeholder satisfaction.

Design, build, and operate scalable AWS data platforms and pipelines (batch/streaming) for analytics and ML. Implement data ingestion, transformation, governance, knowledge graphs, monitoring, and secure access. Optimize architectures, build tooling and dashboards, integrate enterprise systems, and collaborate cross-functionally to ensure data quality, lineage, and maintainability.