Director, AI Engineering
Capital One
AWSAzureCloudOpen SourcePyTorch
Senior Engineer, Applied AI
HackerOne
full-time
Posted on:
Location Type: Remote
Location: Remote • Washington • 🇺🇸 United States
Visit company websiteSalary
💰 $170,000 - $250,000 per year
Job Level
Senior
Tech Stack
AWSAzureCloudGoogle Cloud PlatformGraphQLPyTorchReactRubyRuby on RailsTensorflow
About the role
- Build and evolve our autonomous AI security agent “Hai” with capabilities to plan, reason, and take secure actions including vulnerability detection, threat intelligence generation and automated security analysis
- Build and enhance our AI security agent "Hai" to provide instant security insights, natural language query processing, and actionable recommendations for security teams
- Develop AI red teaming agents and frameworks that help identify vulnerabilities in large language models, generative AI systems, and applied AI deployments
- Collaborate with product teams to integrate AI capabilities that enhance vulnerability discovery, validation, and remediation
- Create APIs and integrations that enable seamless interaction between AI models, security tools, and the broader HackerOne ecosystem
- Partner with cross-functional teams including Product, Security Research, and Customer Success to translate AI innovations into customer-facing security solutions
- Integrate emerging agentic frameworks and LLM-based orchestration tools (e.g., LangChain, Semantic Kernel, AutoGen, OpenAgents) to power stateful AI agents with access to security tools, APIs, and third-party systems
- Stay current with emerging AI security threats, research cutting-edge AI safety techniques, and contribute to the development of industry-leading AI security standards
Requirements
- 5+ years of experience as a software engineer
- Experience building production-grade AI platforms and infrastructure that support multiple AI product teams and applications
- Strong hands-on experience with large language models (LLMs), generative AI, and machine learning frameworks (TensorFlow, PyTorch, Transformers) in production environments
- Expertise in AI platform engineering including model deployment, MLOps pipelines, model serving infrastructure, and shared AI services architecture
- Solid understanding of AI safety and alignment principles, including responsible AI development, bias mitigation, and ethical AI practices
- Familiarity with frameworks like ReAct, AutoGen, or Semantic Kernel for agentic orchestration
- Experience in agent action routing, secure tool usage APIs, and feedback loops for autonomous agents
- Knowledge of prompt engineering, fine-tuning techniques, retrieval-augmented generation (RAG), and advanced LLM optimization strategies
- Background with cloud-based AI/ML services (AWS Bedrock, GCP Vertex AI, Azure ML) and containerization technologies for AI workloads
- Familiarity with Ruby on Rails, GraphQL, React, and experience integrating AI capabilities into existing web applications and APIs.
Benefits
- Health (medical, vision, dental), life, and disability insurance*
- Equity stock options
- Retirement plans
- Paid public holidays and unlimited PTO
- Paid maternity and parental leave
- Leaves of absence (including caregiver leave and leave under CO's Healthy Families and Workplaces Act)
- Employee Assistance Program
- Flexible Work Stipend
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
large language modelsgenerative AImachine learning frameworksTensorFlowPyTorchMLOpsmodel deploymentprompt engineeringfine-tuning techniquesretrieval-augmented generation
Soft skills
collaborationcommunicationproblem-solvinginnovation
