Software Engineering MTS (Cybersecurity)

TL;DR

Software Engineering MTS (Cybersecurity): Building a secure, cloud-native data platform that processes large-scale security signals in real time with an accent on distributed systems, data engineering, and applied AI. Focus on designing LLM- and ML-driven workflows, anomaly detection, risk scoring, agentic remediation, and highly reliable security infrastructure.

Location: Bellevue, Washington, United States

Salary: $117,200–$176,700 annually, excluding bonuses, equity, and benefits.

Company

hirify.global operates within Salesforce’s cloud software ecosystem and develops scalable platform and infrastructure technologies.

What you will do

• Design and architect a secure, highly scalable data platform for security signals from Salesforce products and external environments.
• Build and optimize real-time data pipelines processing application logs, asset data, vulnerability information, identity data, and other security signals.
• Integrate RAG, agentic tool use, anomaly detection, risk scoring, and automated triage and remediation into production systems.
• Establish data governance, quality, security, and compliance frameworks for enterprise risk management.
• Collaborate with Engineering, Security Operations, Risk Management, Product Security, and Data Science teams.
• Provide technical leadership through code reviews, mentoring, secure AI-assisted development, and cloud-native architecture practices.

Requirements

• At least 2 years of industry experience, including 2 years in SaaS, PaaS, or IaaS software development.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or equivalent experience.
• Experience with distributed systems, high-availability infrastructure, Docker, EKS, Infrastructure-as-Code, Terraform, and Puppet.
• Proficiency with Apache Spark, Kafka, Hadoop, SQL/NoSQL, and Python, Golang, Java, or Scala.
• Strong knowledge of security concepts including SSO, SAML, OAuth, TLS, certificates, and PKI, plus Linux software development.
• Production experience integrating LLMs or ML models, including at least two areas such as RAG, agent/tool-use frameworks, prompt engineering, evaluations, fine-tuning, or vector stores.

Nice to have

• AI/ML experience in anomaly detection, alert triage, vulnerability prioritization, or SOC automation.
• Experience with MCP, agentic workflows, vector databases, and embedding-based retrieval.
• Knowledge of LLM cost and latency optimization, guardrails, prompt-injection defense, and evaluation frameworks.

Culture & Benefits

• Agile development with daily syncs and cross-functional collaboration.
• Opportunities for technical growth, mentoring, and meaningful security impact.
• Time off programs, medical, dental, vision, mental health support, and paid parental leave.
• Life and disability insurance, 401(k), and employee stock purchasing program.
• Emphasis on secure engineering, responsible AI adoption, continuous learning, and engineering excellence.