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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in developing AI-powered applications and services for cybersecurity, utilizing Python, AI agents, and Retrieval Augmented Generation (RAG) techniques. Proficient in software engineering practices, including CI/CD and API-driven architectures, while ensuring security and scalability.
Highest-signal resume keywords
Python-Based Solutions DevelopmentAI Application DevelopmentRetrieval Augmented Generation (RAG)Security Automation WorkflowsMicrosoft AI Engineer Certification
Tech Stack
Tools & technologiesAbout the role
Key responsibilities & impact- Design, build, and operationalize AI-powered applications, copilots, and autonomous agents for cybersecurity use cases
- Develop Retrieval Augmented Generation (RAG) solutions leveraging enterprise knowledge sources and security data
- Create MCP-enabled integrations connecting AI agents with security tools, workflows, and enterprise platforms
- Build secure and scalable AI services using modern software engineering and DevOps practices
- Enhance self-hosted AI infrastructure, model serving platforms, and AI observability capabilities
- Develop security automation workflows that improve analyst productivity and reduce operational overhead
- Partner with Security Operations, Risk, Product Security, Vulnerability Management, and Threat Intelligence teams to deliver AI-driven solutions
Requirements
What you’ll need- Master's degree OR Bachelor's degree in Computer Science, Artificial Intelligence, Software Engineering, Cyber Security, Data Science, or a related field
- 5+ years of software engineering, AI engineering, machine learning engineering, or platform engineering experience
- Development of Python-based solutions and API-driven architectures
- Building and deploying production-grade AI applications and services
- Application of Large Language Models (LLMs), AI agents, prompt engineering, Retrieval Augmented Generation (RAG), vector databases, and semantic search
- Application of software engineering practices including CI/CD, version control, testing, and code quality processes
- Analytical troubleshooting, problem solving, communication, and stakeholder management capabilities
- Experience with self-hosted LLM environments and enterprise AI platforms
- Experience developing agentic workflows and multi-agent systems
- Knowledge of AI security risks including prompt injection, model abuse, data leakage, and secure agent design
- Experience building AI solutions for cybersecurity use cases
- Experience integrating security tools through MCP or API frameworks
- Certifications: Microsoft AI Engineer, Azure AI Engineer, AWS ML, CISSP, or related certifications
Benefits
Comp & perks- Flexible work environment
- Culture focused on individual growth, well-being, and belonging
- Employee diversity, respect, and inclusion commitment
- Accommodation measures for disability or other needs
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Software EngineeringAI EngineeringMachine Learning EngineeringPlatform EngineeringLarge Language Models (LLMs)API-Driven ArchitecturesCI/CD PracticesAnalytical TroubleshootingProblem SolvingAgentic Workflows Development
Soft Skills
CommunicationStakeholder Management
Tools & Technologies
MCP IntegrationsSelf-Hosted LLM EnvironmentsEnterprise AI PlatformsSecurity Tools Integration
Certifications & Qualifications
Microsoft AI EngineerAzure AI EngineerAWS MLCISSP
Industry Keywords
CybersecurityAI Security RisksModel AbuseData LeakageSecure Agent Design