Qualys
Senior Security Engineer, AI/ML
Foster City, USA · Senior
Sponsorship not specified$115k-$140kDetected 112 days ago
PythonSQLVector DatabasesAWSGCPAzureCloud PlatformsCI/CDMachine LearningDeep LearningTensorFlowPyTorchscikit-learnPandasNLPLLMsRAGAgentic AIMLOpsCybersecurityPenetration TestingDetection EngineeringSupply ChainResearch
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odds of building a lasting career here
53Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role75
Entry-level history0
PERM / green-card track0
Lottery odds (Level III)83
Fits your clock70
Sponsors, but it's cap-subject — you still face the weighted lottery (~45% per draw at Level III). Good if you win; have a cap-exempt backup on your list.
Lottery odds assume a STEM candidate.
Personalize to your clock →Employer immigration record
from this employer's Department of Labor filings
Green-card follow-through: 100%
Of 15 labor certifications old enough to have been used, 0 expired without the employer filing the next step. Median time from filing to decision: 497 days.100% of their filings were for a worker who already held the job.Only certifications past the 180-day window are counted — recent ones cannot have expired yet.
Files H-1B transfers
6 transfer filings in the last year, covering 6 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.
Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.
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About the role
- With a strong focus on innovation and scale, Qualys empowers organizations to achieve continuous security and compliance through real-time visibility and analytics.
- This is a senior, dual-mandate role for an engineer who is equally comfortable orchestrating multi-agent pipelines and RAG architectures as they are tearing them apart to find weaknesses.
- Our Work Environment - Collaborative & Transparent: We use virtual collaboration and pairing tools to share ideas openly.
Responsibilities
- Build and deploy GenAI applications using LangChain, LlamaIndex, or similar frameworks, and orchestrate agentic AI workflows with tools such as AutoGen, CrewAI, or custom agent-based architectures.
- Implement and optimize RAG pipelines using embeddings and vector databases (e.g., FAISS, Pinecone, Qdrant ), with security and data-leakage controls built in from the start.
- Design and execute offensive security assessments and red teaming campaigns against GenAI and ML-powered systems, including the agentic pipelines built in-house.
- Contribute to and build internal tooling for scanning, fuzzing, and automating LLM vulnerability discovery.
- Lead & Communicate
- Collaborate cross-functionally with product and engineering teams to design secure AI-powered features and define hardening strategies.
- Develop proof-of-concepts, technical whitepapers, or blog posts on emerging threats and best practices
- Develop proof-of-concepts, technical whitepapers, or blog posts on emerging threats and best practices; monitor threat intelligence and academic research on AI model security and supply chain risks.
Requirements
- Experience training ML models using Scikit-learn, TensorFlow, or PyTorch, and a strong working knowledge of LLM architectures (transformers, embeddings, fine-tuning, RAG).
- Hands-on experience with LangChain, LlamaIndex, or other GenAI frameworks, and with building multi-agent or autonomous AI workflows.
- Ability to analyze logs, API interactions, inference responses, and prompt chains to identify anomalous or risky behavior.
Nice to have
- Background in AI/ML security red teaming or adversarial ML.
- Knowledge of vector database risks, insecure RAG pipelines, model fingerprinting, and AI model supply chain attacks.
- Experience using or contributing to tools such as AutoGen, CrewAI, MetaGPT, Guardrails.ai, LLM Guard, or Tracer.
- Familiarity with LLMs such as GPT-4, Claude, Mistral, LLaMA, or Falcon, and integrating them via APIs.
- Experience with cloud platforms (AWS, GCP, Azure), containerized deployments, and MLOps tooling for monitoring, retraining, and CI/CD automation.
- Familiarity with Secure SDLC and threat modeling frameworks (e.g., STRIDE, MITRE ATLAS) and AI-specific security checklists.
- Publications or presentations at conferences such as Black Hat, DEF CON, USENIX, NeurIPS, or OWASP, and contributions to AI/ML projects in security, compliance, or enterprise applications.
- Our Work Environment
Compensation
- The salary range for this position is $115,000 - $140,000 per year.
- Final compensation will be determined based on several factors, including but not limited to skills, relevant experience, and work location.
- Please note this range reflects base salary and does not include incentive compensation or potential equity grants.
Benefits
- Design, train, and evaluate ML models from scratch, spanning both classical ML and deep learning, and develop end-to-end pipelines for ingestion, preprocessing, training, evaluation, and deployment.
- We offer a comprehensive benefits package, including healthcare, retirement plans, and more.
- We also offer a comprehensive and highly competitive benefits package.
Company info
- Company Overview Qualys is a leading provider of cloud-based security and compliance solutions, processing vast amounts of data to help our global customers secure their networks, devices, and applications.
- As we continue to grow, we are looking for passionate and skilled professionals to join our mission in redefining the future of cybersecurity.
- Position Overview We are seeking a Senior Security Engineer - AI/ML who sits at the intersection of hands-on AI/ML engineering and offensive security research.
Equal opportunity
- Qualys is an Equal Opportunity Employer, please see our EEO policy.
This listing is sourced directly from Qualys's careers page and normalized into a canonical job model.