Senior Backend Engineer (Cloud)
Dead Line: May 4, 2022
- Architect, develop and manage high-performing, reliable, and scalable backend systems
- Develop secure and fit-for-purpose data pipelines for our AI ecosystem
- Design and develop database schemas and interfaces
- Understand and contribute to the product vision and roadmap
- Write production-quality code for medium to large features and services independently
- Review requirements, specifications, and technical documents to provide timely and meaningful feedback
- Lead code reviews, providing constructive feedback
- Mentor junior engineers and interns
- Assist in the recruitment of talent
- BS/MS/PhD in Computer Science or a related field.
- 3+ years of professional software engineering experience.
- Experience with designing and building high-performing, reliable, and scalable backend systems.
- Experience with cloud technologies, e.g. Docker, Kubernetes, AWS, Azure, GCP.
- Experience with creating products that support ML workflow.
- Experience with open-source and commercial products in the Data/MLOps and cloud infrastructure space.
- Demonstrated experience in object-oriented and/or functional programming languages: JavaScript, Python, Swift, C++
- Strong database experience (NoSQL, SQL)
- Good knowledge of GraphQL, REST
- Comfortable working in a fast-paced, highly collaborative, dynamic work environment
- Excellent communication skills
- Experience with Agile Development and testing methodologies and best practices
- Stay current with industry trends, making recommendations as needed to help the company excel.
- Secure and skilled at working in tandem with a team of engineers, or alone as required.
- Experience with software security and systems that handle sensitive data
- Experience with DevSecOps
- Experience with HIPAA and/or FDA compliance
- Experience with testing (unit, integration, and e2e)
- Experience with one or more frameworks such as Django, Flask, Node.js, React
- Experience with building large scale data pipelines with Kafka, Spark.
- Familiarity with the design and internals of common ML frameworks, such as PyTorch, Tensorflow, XGBoost, etc.
- Familiarity with infrastructure provisioning, cloud services, cloud security & cost management in public cloud environments like AWS, GCP, or Azure.
- Experience with building open-source projects and working with the open-source community
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