Software Engineering LMTS (AI/ML)

TL;DR

Software Engineering LMTS (AI/ML): Building a secure, cloud-native security data platform that ingests and processes enterprise security signals with an accent on distributed systems, big data processing, cybersecurity, and applied AI. Focus on designing LLM- and ML-driven workflows for anomaly detection, risk scoring, automated triage, and remediation while ensuring scalability, reliability, governance, and secure agent design.

Location: Bellevue, Washington, United States

Salary: $172,500–$260,100 annually in base salary, excluding bonus, equity, and benefits.

Company

hirify.global provides cloud application development and platform services as part of Salesforce.

What you will do

• Lead the architecture and implementation of a scalable, fault-tolerant security data platform.
• Build data pipelines that collect and process asset, vulnerability, identity, access, and security signals from Salesforce platforms and external environments.
• Integrate LLM- and ML-based capabilities, including RAG, agentic tool use, anomaly detection, risk scoring, and automated remediation.
• 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 architecture guidance, code reviews, mentoring, and safe adoption of AI-assisted development tools.

Requirements

• 10+ years of industry experience, including 5+ years in SaaS, PaaS, or IaaS software development.
• Expertise in high-scale distributed systems, cloud-native architecture, high availability, Docker, EKS, IaC, Terraform, and Puppet.
• Experience with Apache Spark, Kafka, Hadoop, SQL/NoSQL, and Python, Golang, or Java/Scala.
• Strong knowledge of API design, Linux, authentication and authorization, SSO, SAML, OAuth, TLS, certificates, and PKI.
• Production experience integrating LLMs or ML models, including at least two of RAG, agent/tool-use frameworks, prompt engineering, LLM evaluations, fine-tuning, or vector stores.
• Fluent use of AI-assisted coding tools such as Claude Code, Cursor, or Copilot, plus strong communication, mentoring, and delivery skills.

Nice to have

• Experience applying AI/ML to security use cases such as anomaly detection, alert triage, vulnerability prioritization, or SOC automation.
• Experience with MCP, agentic workflows, vector databases, embeddings, LLM cost and latency optimization, guardrails, or prompt-injection defense.

Culture & Benefits

• Technical leadership role with visibility into enterprise security strategy and meaningful business impact.
• Opportunities for professional development across cloud-native systems, cybersecurity, big data, and applied AI.
• Benefits include time-off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and employee stock purchasing.
• Work in an Agile environment with a focus on engineering excellence, continuous learning, innovation, and secure development practices.