About CBTW

  As a global tech company, we empower businesses with tailored tech and business solutions that drive innovation and sustainable growth. With over 3,000 experts across 21 countries, we deliver results through flexible engagement models—whether augmenting teams, managing complex projects, or building long-term operations. We specialize in Strategy & Governance, Product Design & Growth, Software Engineering, Data Analytics & AI, Cloud & Enterprise Platforms, Cybersecurity, and industry-specific solutions for Banking, Life Sciences, and Smart Industrial sectors. Guided by our commitment to building a better world, we dedicate time, resources, and expertise to education projects, creating a lasting impact on our teams, communities, and planet.

Required:

• 2+ years of experience building and deploying applications using one or more AWS cloud technologies.

• Full-stack engineering experience related to designing APIs & microservices, integration among AWS databases, backend services, and frontend web & apps.

• Experience with Data Science, AI/ML pipelines on Amazon Sagemaker, Bedrock, or other cloud environments.

• Data Engineering and DevOps skills in automation and virtualization related to model deployment and scaling.

• Familiarity with different microservice deployment methodologies, including A/B testing, blue-green, and canary deployments.

• Proficient in Python or other programming languages used for developing Data Science, AI/ML models.

• A commitment to ongoing learning and development.

• Proficient in verbal English.

Desirable:

• Experience building AI/ML-driven customer-facing products in a fast-moving B2C e-commerce or marketplace environment.

• Experience working with real-time data streams, Feature Store, and/or Data Lake.

• Relevant knowledge in one or a few areas of Generative AI, LLMs, Machine Learning, Data Science, algorithms, statistics, optimizations, and hypothesis testing.

• Previous people management experience or a desire to become a technical and people lead.

Attributes:

• Detail-oriented with good discipline and a curious mindset.

• Result-driven with a focus on delivering measurable business outcomes.

• Be an entrepreneur – always looking for new opportunities to improve practices for the AI team.

• Provide the software engineering and best practices required around the production of a Data Science or AI model application from start to finish.
• Bring the team’s models to life by working with Engineering and Product teams to develop real-time customer-facing products empowered by the models.
• Build integration between model serving endpoints with front-end web and mobile applications, as well as other services that consume the model output.
• Ensure integration between the model training/inference jobs and databases, including real-time data streams.
• Demonstrate the value of Data Science & AI to the business by quickly building POCs and prototypes.
• Build scalable live A/B testing architecture and implementation around model deployment to rapidly and continuously experiment with new models.
• Collaborate with Data Scientists and other Engineering teams to build platform capabilities that enable efficient model training, deployment, and CI/CD pipelines.
• Support what the team builds by implementing robust testing, monitoring, logging, and alerting.
• Work in a global and cross-functional team, acting as a thought leader and engineering expert to help shape the design and production of future products.