Software Engineering LMTS/SMTS, Salesforce

• The ideal candidate has strong software engineering skills, with a passion for designing secure, large-scale, distributed systems
• Knowledge or experience in AI/ML or MLOps is valuable
• If you are excited about pushing the boundaries of security and working with advanced technologies, we encourage you to apply!
• Bachelor’s degree in Computer Science, Software Engineering, or related field (or equivalent experience)
• 3–8 years of professional software development experience
• Proficiency in one or more programming languages: Python, Go, Java
• Experience with distributed systems, SaaS platforms, microservices, and REST/gRPC APIs
• Familiarity with Kubernetes, Docker, Terraform, and cloud-native architectures
• Knowledge of software security best practices (e.g., OWASP Top 10, Zero Trust, MFA)
• Strong problem-solving, debugging, and collaboration skills
• Knowledge and/or experience with MLOps or AI/ML concepts, with willingness to grow further in this area
• Experience working in a large-scale, enterprise environment
• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience

Desirable

• Auto-IAM team delivers next-generation Identity and Access Management (IAM) platform that strengthens Enterprise Security
• The platform unifies security, scalability, and compliance by using AI and machine learning to enable advanced features like adaptive authentication, anomaly detection, and predictive security insights
• The threat data fabric consolidates various Enterprise scale data to enable autonomous decision-making and reduce manual work
• We are seeking talented Software Engineers to join our team in building a next-generation Enterprise Security and IAM platform
• In this role, you will develop and optimize scalable solutions, collaborate with cross-functional teams, and contribute to the integration of intelligent, AI-driven capabilities that enhance enterprise security
• Curiosity and willingness to learn in this ever changing area is also equally important
• Analyze large-scale structured and unstructured datasets to identify trends, anomalies, risks, and opportunities in security and AI-powered tools
• Build, curate, and maintain datasets; ensure data integrity across multiple sources for testing and model development
• Develop, optimize, and test machine learning models (predictive, generative, NLP) and support MLOps workflows for deployment, monitoring, and integration into IAM systems
• Partner with data scientists to productionize AI/ML models for risk-based access control, anomaly detection, and identity analytics
• Design and implement quantitative metrics, dashboards, and visualizations to communicate insights and track key performance indicators (KPIs)
• Monitor log and telemetry data to proactively detect potential harms, threats, and misconfigurations
• Build and deploy containerized applications using Kubernetes, Docker, Terraform, and modern CI/CD practices
• Write clean, maintainable, and efficient code in languages such as Python, Go, and Java
• Collaborate with cross-functional teams to integrate IAM features such as Zero Trust, adaptive authentication, and device attestation
• Troubleshoot and resolve software, infrastructure, and platform-related issues across diverse environments