Sr. Software Engineer, Backend

Platform Architecture & Back-End Development

Architect and implement microservices-based platforms with a strong focus on scalability, performance, and reliability. Develop core services using Python, Java, and Spring Boot, and ensure seamless integration with AI and data workflows.

Cloud & Containerization

Build and deploy applications on AWS leveraging services for compute, storage, and networking. Implement containerized deployments using Docker and Kubernetes to support CI/CD pipelines and automated scaling.

Data Systems & ETL

Collaborate with data engineering teams to design and optimize SQL-based data systems, ETL pipelines, and feature workflows that feed AI models at scale.

Reliability & Observability

Drive platform reliability through monitoring, logging, and performance tuning. Implement best practices for CI/CD, automated testing, and infrastructure-as-code.

AI Tooling & Integration

Build developer tools and abstractions for integrating LLMs and AI models, including orchestration services and prompting frameworks.

Innovation & Scalability

Push the boundaries of platform scalability and performance, ensuring systems can handle large-scale data processing and high-throughput workloads.

What You Bring

• Bachelor’s or Master’s in Computer Science, Engineering, or related field
• 5+ years of experience in back-end software engineering, with proven ability to design and scale distributed systems
• Strong proficiency in Python and Java, with experience in Spring Boot and object-oriented design
• Hands-on experience with AWS cloud services, Docker, and Kubernetes in production environments
• Solid understanding of SQL databases, data modeling, and performance optimization
• Familiarity with microservices architecture, CI/CD pipelines, and infrastructure automation
• Excellent communication and collaboration skills across engineering and product teams

Nice to Have

• Experience with large-scale data pipelines (e.g., Apache Spark, Kafka)
• Knowledge of MLOps principles and AI/ML frameworks (TensorFlow, PyTorch)
• Certifications in cloud platforms or container orchestration
• Awareness of AI ethics, data privacy, and security best practices

Pay

The anticipated annual pay scale for this position is $150,000-$250,000. Actual salaries will vary depending on factors including but not limited to location, experience, and performance.