Senior Security Engineer, AI/ML

Location: Foster City, United States

Salary: $115,000–$140,000 per year in base compensation, excluding incentive compensation and potential equity grants.

Company

hirify.global provides cloud-based security and compliance solutions that process large-scale data to help organizations secure networks, devices, and applications.

What you will do

• Build and deploy GenAI applications and agentic workflows using frameworks such as LangChain, LlamaIndex, AutoGen, CrewAI, or custom architectures.
• Design, train, evaluate, and deploy classical ML and deep learning models through end-to-end data and ML pipelines.
• Develop secure RAG pipelines with embeddings and vector databases, including data-leakage controls.
• Build Python backend APIs for model serving, data processing, and cloud integration; monitor production performance, latency, and accuracy.
• Research LLM and AI vulnerabilities, including prompt injection, jailbreaks, data leakage, model theft, and adversarial attacks.
• Conduct red-team assessments, identify emerging threat vectors, and create tooling for scanning, fuzzing, and automating LLM vulnerability discovery.

Requirements

• 6+ years of combined experience in software engineering, machine learning, security research, penetration testing, or exploit development, with a focus on application or cloud security.
• Strong Python programming skills, including backend APIs, scripting, automation, and proof-of-concept development.
• Experience training ML models with Scikit-learn, TensorFlow, or PyTorch, plus knowledge of transformers, embeddings, fine-tuning, and RAG.
• Hands-on experience with GenAI frameworks and multi-agent or autonomous AI workflows.
• Knowledge of GenAI risks and LLM deployment scenarios, including prompt injection, model evasion, hallucination-based exploits, data leakage, model theft, and model-serving threat surfaces.
• Working knowledge of SQL, Pandas, large-scale data processing, Agile ML development, security research ethics, and responsible disclosure.

Nice to have

• Experience in AI/ML security red teaming, adversarial ML, vector database security, insecure RAG pipelines, model fingerprinting, or AI supply chain attacks.
• Experience with AutoGen, CrewAI, MetaGPT, Guardrails.ai, LLM Guard, or Tracer.
• Knowledge of major LLMs, cloud platforms, containers, MLOps, Secure SDLC, threat modeling, and AI-specific security frameworks.
• Security or AI/ML publications, conference presentations, or project contributions.

Culture & Benefits

• Collaborative environment using virtual collaboration and pairing tools; siloed work is discouraged.
• Agile and flexible delivery focused on incremental value.
• Diverse, inclusive, and transparent working environment.
• Opportunities for mentorship, certifications, professional growth, and exposure to security research.
• Comprehensive benefits package including healthcare and retirement plans.