Staff Software Engineer

Job Description Summary

We are seeking a Staff Software Engineer to lead the design, development, and evolution of our cloud-native, AI/ML-enabled multi-tenant SaaS platform. This role combines full-stack engineering, cloud infrastructure, AI/ML integration, and database expertise.
You will influence architecture, mentor engineers, and deliver end-to-end, data-driven, intelligent applications. You will collaborate closely with product managers, data scientists, and platform teams to define and implement scalable, secure, and AI-enhanced systems.

Job Description

Full-Stack Development

• Build and maintain backend services using Java and Spring Boot, including microservices and RESTful APIs.
• Develop modern, responsive frontend applications using React, TypeScript, and JavaScript.
• Deliver end-to-end solutions spanning UI, backend, cloud infrastructure, and AI/ML integrations.
• Apply distributed systems, system design, and multi-tenant SaaS best practices.

• Design, optimize, and maintain SQL (RDS, Aurora) and NoSQL (DynamoDB) databases.
• Build and manage data pipelines for structured and unstructured data.
• Ensure data security, multi-tenancy, and query optimization.

• Collaborate with data science teams to integrate ML models into SaaS products.
• Develop REST APIs, microservices, or SDKs to serve ML/AI models to end-users.
• Implement real-time or batch AI/ML inference pipelines on cloud infrastructure.
• Familiarity with AWS AI/ML services (SageMaker, Bedrock, Comprehend, etc.) is a plus.

• Deploy and operate applications on AWS (EKS, EC2, S3, RDS, DynamoDB, Lambda).
• Containerize applications with Docker and orchestrate with Kubernetes.
• Build and maintain CI/CD pipelines, monitoring, and observability.
• Ensure scalability, reliability, security, and cost efficiency.

• Influence platform and product strategy in a multi-tenant SaaS environment.

• Own architecture and technical decision-making across frontend, backend, cloud, and AI/ML integrations.
• Mentor senior and mid-level engineers, setting engineering standards and best practices.
• Drive adoption of observability, security, and performance optimizations across teams.