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Job Description
Role Summary
We are seeking a Senior AI Engineer to help build next-generation cybersecurity AI products for enterprise security teams.
This is a hands-on individual contributor role for an engineer who combines strong AI engineering capability, practical software development skills, and a strong interest in cybersecurity. You will report to the Director, Cybersecurity AI Product and work as part of a newly formed product development team focused on building and operating agentic solutions that help users investigate threats, triage alerts, automate security workflows, analyze vulnerabilities, and make better security decisions.
The ideal candidate is AI-native, product-minded, proactive, and comfortable working through ambiguity. You should be able to learn quickly, experiment with new AI technologies, build reliable product features, and translate customer problems into practical AI-driven solutions.
This role requires hands-on experience with LLM applications, agentic AI systems, retrieval-augmented generation, tool orchestration, context management, model evaluation, cloud-native software engineering, APIs, and secure software development. Familiarity with cybersecurity concepts, security operations, cloud security, or threat intelligence is strongly preferred.
Key Responsibilities:
- Build Cybersecurity AI Products Apply Strong AI Engineering Practices Develop Production-Grade Software Continuously Learn, Research and Evaluate Emerging AI technologies
Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager.
Qualifications
Basic Qualifications:
- 8+ years of relevant work experience with a Bachelor’s Degree or at least 5 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 2 years of work experience with a PhD, OR 11+ years of relevant work experience.
Preferred Qualifications:
Graduate degree (Master’s or Ph.D.) in computer science or other related fields
Experience building AI agents, LLM applications, copilots, automation systems, or RAG-based products.
Working knowledge of cybersecurity principles, secure software development, and common vulnerabilities.
Familiarity with one or more areas such as:
- Application security
- Cloud security
- Identity and access management
- Security operations
- Vulnerability management
- Threat intelligence
- Incident response
- SIEM/SOAR workflows
Familiarity with AI security risks, including prompt injection, data leakage, hallucination, unsafe tool use, and adversarial inputs.
Experience with evaluation methods for LLM systems, including golden datasets, human review workflows, offline evaluation, online evaluation, and regression testing.
Experience with Kubernetes, infrastructure as code, observability platforms, secrets management, or cloud-native security.
Familiarity with security frameworks such as MITRE ATT&CK, OWASP, NIST Cybersecurity Framework, CIS Controls, or ISO 27001.
Experience working in early-stage product teams, startups, innovation teams, or ambiguous product incubation environments.
AI Engineering:
Practical experience with LLM applications, AI workflow automation, AI assistants, copilots, or agentic AI systems.
Familiarity with concepts such as:
- Prompt engineering
- System prompts and instruction design
- Retrieval-augmented generation
- Vector search
- Embeddings
- Tool calling
- Function orchestration
- Context management
- Agent memory
- Evaluation datasets
- Model benchmarking
- Feedback loops
Experience with agentic AI frameworks or tools such as:
- LangChain
- LlamaIndex
- Semantic Kernel
- AutoGen
- CrewAI
- OpenAI Assistants / Responses-style APIs
- Vector databases
- Knowledge graphs
- Model evaluation frameworks
Ability to evaluate AI outputs objectively and improve quality, safety, reliability, latency, and cost.
Experience using commercial or open-source AI models and APIs.
Demonstrated ability to use AI tools in everyday work for coding, debugging, research, documentation, testing, or productivity improvement.
Software Engineering:
Strong programming ability in one or more languages such as:
- Python
- TypeScript / Node.js
- Go
- Java
- C#
- Rust
Experience building backend services, APIs, data pipelines, integrations, or cloud-native applications.
Familiarity with web applications, distributed systems, databases, CI/CD pipelines, logging, monitoring, and automated testing.
Ability to write clean, maintainable, secure, and production-ready code.
Experience participating in design reviews, code reviews, and production troubleshooting.
Cloud and Infrastructure:
- Experience developing or deploying applications on cloud platforms such as AWS and/or Microsoft Azure.
- Familiarity with containers, serverless services, managed databases, event-driven systems, queues, object storage, and cloud identity concepts.
- Understanding of observability, deployment automation, environment configuration, and operational reliability.
- Awareness of cloud security principles, IAM, secrets management, and secure configuration.
Leadership Qualities:
- Strong ownership mindset and accountability for outcomes.
- Proactive approach to identifying problems and proposing solutions.
- Customer-obsessed mindset with focus on practical user value.
- Comfortable dealing with ambiguity and evolving requirements.
- Strong analytical and problem-solving skills.
- Clear written and verbal communication skills.
- Strong habit of continuous learning, experimentation, and knowledge sharing.
- Ability to work independently and collaborate effectively in a small, fast-moving team.
Visa is an EEO Employer
Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.