Senior Full Stack Software Engineer

Summary

Join SnapLogic as a Full Stack Software Engineer with a data science mindset to modernize enterprise systems using AI/ML and cloud-native technologies. You will collaborate with various teams to build scalable software and data-driven features for seamless legacy modernization. This remote role involves building full-stack web applications, supporting legacy-to-cloud migration, developing machine learning capabilities, and working on data pipelines. The position requires 3–6 years of full-stack software engineering experience, backend skills in Python, Java, or Scala, and experience with ML/data science techniques. You will contribute to scalable architecture across cloud and hybrid environments and work with infrastructure-as-code. This is a high-growth opportunity to contribute to enterprise transformation in the age of AI.

Requirements

• 3–6 years of experience in full stack software engineering
• Solid backend skills in Python, Java, or Scala, with experience developing modern web UIs using React or TypeScript
• 1–2 years of experience applying ML or data science techniques to real-world problems
• Knowledge of cloud-native development and microservices architecture
• Experience building and deploying containerized microservices in Kubernetes or similar platforms
• Experience with infrastructure-as-code, especially Terraform
• Strong documentation and communication skills — you’re comfortable writing specs, collaborating cross-functionally, and demoing work to stakeholders
• Passion for learning, experimentation, and building user-friendly tools

Responsibilities

• Build and maintain full stack web applications and backend services that support enterprise data and application integration
• Support legacy-to-cloud modernization by building tools that simplify migration and transformation
• Collaborate across engineering and product to develop user-facing features and modernization workflows
• Contribute to scalable architecture across cloud and hybrid environments (AWS, Kubernetes, Docker)
• Design and develop machine learning-powered capabilities like smart data mapping, anomaly detection, and automation recommendations
• Work on data pipelines to support model training, feature engineering, and analytics
• Help integrate ML models into production systems in ways that improve user experience and reduce manual effort

Preferred Qualifications

• Familiarity with the challenges of legacy systems, integration, or migration projects
• Experience working with LLMs or GenAI in enterprise software
• Knowledge of enterprise integration platforms (e.g., MuleSoft, Informatica)
• Exposure to mainframe systems, ERP migrations, or low-code/no-code platforms
• Experience working directly with customers or external stakeholders to gather feedback and rapidly iterate on product features
• Interest in contributing to technical blogs, open source, or conferences

Benefits

• $130,000 - $160,000 a year
• Annual cash bonuses or commissions
• Stock options
• Comprehensive benefits package