SFDC with agentic AI exp

American IT Systems•San Jose, CA

3d•Onsite

About The Position

We are seeking a highly talented Software Engineer to join our team in building a next-generation Enterprise Security and IAM platform. 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. 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. If you are excited about pushing the boundaries of security and working with advanced technologies, we encourage you to apply!

Requirements

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.

Nice To Haves

Exposure to MLOps pipelines (model training, deployment, monitoring).
Familiarity with ML frameworks (TensorFlow, PyTorch, scikit-learn) or cloud AI services (AWS SageMaker, Bedrock, Salesforce Cloud AI).
Experience with IAM, Cybersecurity, or compliance

Responsibilities

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.