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Staff Consultant – GDS Cyber, Frontier AI Layered Defense
EYStaff / Junior AI Security Engineer supporting the design and implementation of security for AI-enabled systems. Working with senior engineers to address frontier AI risks and safeguards in enterprise environments.
Tech Stack
Tools & technologiesAWSAzureCloudCyber SecurityGoogle Cloud PlatformPythonSQL
About the role
Key responsibilities & impact- Support implementation of layered defense controls for LLM, RAG, and agentic AI use cases, including input handling, context isolation, tool-use boundaries, response checks, access controls, and monitoring.
- Assist in building and testing AI applications using frameworks such as LangChain, LangGraph, LlamaIndex, AutoGen, OpenAI-compatible APIs, and related orchestration tools.
- Configure and validate basic AI application safeguards, including prompt handling, response constraints, sensitive data handling checks, and escalation paths for uncertain or high-impact outputs.
- Support secure RAG implementation by helping validate data ingestion, retrieval boundaries, embedding and vector store access, source attribution, and secure handling of structured and unstructured enterprise data.
- Execute predefined misuse-resistance and scenario validation checks, including attempts to bypass instructions, expose hidden context, trigger unintended actions, or produce unsafe or unreliable outputs.
- Review AI system logs, traces, prompts, outputs, tool calls, and telemetry to identify anomalies, unexpected behavior, and potential security issues for escalation.
- Support secure integration of AI systems with enterprise APIs, identity platforms, cloud services, workflow tools, and knowledge repositories under senior guidance.
- Assist in documenting validation results, control observations, implementation notes, remediation actions, and reusable delivery patterns.
- Contribute to automation scripts, test harnesses, and repeatable playbooks for AI application validation and continuous monitoring.
- Follow secure coding practices, data protection requirements, internal standards, and responsible technology expectations while working on AI applications and integrations.
- Stay current on emerging frontier AI risks, AI application security patterns, resilience testing methods, and layered defense practices, and apply learnings to project delivery.
Requirements
What you’ll need- 0–3 years of experience in software development, cybersecurity, AI/ML, data engineering, cloud engineering, or related academic/project work
- Foundational understanding of AI/ML concepts, including LLMs, prompts, embeddings, tokens, vector databases, RAG, and basic agent workflows
- Familiarity with Python and basic scripting for automation, testing, data processing, or API integration
- Working knowledge of SQL and basic data handling concepts, including structured and unstructured data sources
- Awareness of AI application risks such as unintended information exposure, data leakage, unreliable outputs, unsafe tool use, insecure integrations, model misuse, and over-permissive automation
- Foundational knowledge of cybersecurity concepts including authentication, authorization, IAM, API security, secrets handling, secure coding, logging, and vulnerability management
- Exposure to cloud environments such as Azure, AWS, or GCP, with basic understanding of secure deployment and access configuration
- Familiarity with AI or application development frameworks such as LangChain, LangGraph, LlamaIndex, AutoGen, OpenAI APIs, or comparable tools is preferred
- Basic understanding of CI/CD pipelines, version control, software testing, and secure software development lifecycle practices
- Ability to follow structured validation plans, implement predefined controls, document observations, and escalate risks clearly
- Strong communication skills, attention to detail, and willingness to learn in a fast-evolving frontier AI security domain.
Benefits
Comp & perks- Competitive salary
- Flexible working hours
- Professional development
- Work from home options
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
AI Application ValidationData ProcessingSecure Coding PracticesAutomation ScriptingVersion ControlCI/CD PipelinesPrompt HandlingResponse ConstraintsData Leakage AwarenessVulnerability Management
Soft Skills
Strong Communication SkillsAttention to DetailWillingness to Learn