AI Engineer

Whitespace

Agentic AI Engineer developing advanced AI agents focused on cybersecurity applications for national security. Join a cutting-edge team at Whitespace using machine learning solutions.

Posted 4/15/2026full-timeRemote • California, District of Columbia, Virginia • 🇺🇸 United StatesMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

CloudCyber SecurityDistributed SystemsPythonPyTorch

About the role

Key responsibilities & impact

Architect, develop, and deploy advanced autonomous AI agents tailored for cybersecurity applications.
Define and implement intelligent agent systems capable of real-time decision-making and adaptive threat responses.
Collaborate cross-functionally with product managers, engineers, and analysts to translate innovative concepts into robust solutions.
Mentor and guide engineering teams on best practices in developing agent-based AI solutions.
Continuously evaluate, test, and enhance the capabilities and performance of agentic systems within Whitespace’s ecosystem.
Drive technical excellence and promote engineering best practices within the AI team.

Requirements

What you’ll need

A bachelor's or master’s degree in Computer Science, AI, Machine Learning, or a related field with at least 5 years of related experience. Will consider experience in lieu of a degree.
Strong proficiency in Python, with experience in relevant libraries, frameworks, and technologies such as FastAPI, asyncio, and PyTorch.
Deep understanding of agent frameworks and tools (e.g., OpenAI Agents SDK, autogen, Google ADK/A2A, LangGraph, etc.).
Proven experience developing in Python and deploying robust AI/ML solutions, with specific expertise in autonomous agents.
Direct experience integrating generative AI models (OpenAI, Anthropic, Google Gemini, LLaMA) into practical agentic systems.
Demonstrated ability to design scalable, distributed systems and cloud-native architectures.
Extensive experience in prompt engineering and fine tuning LLM models.
Ability to design and implement agentic frameworks and architectures.
Knowledge of techniques for grounding generative models with external knowledge sources (e.g., retrieval-augmented generation, Knowledge graphs, etc.)
Familiarity with MLOps principles and tools for model deployment and monitoring.
Understanding of the security implications and mitigation strategies for generative AI and agentic systems.
Excellent collaboration, mentorship, and communication skills, enabling you to collaborate effectively with distributed teams.
Excellent communication skills, both verbal and written, to convey technical concepts to non-technical stakeholders.

Benefits

Comp & perks

Medical, Dental, and Vision plans
Unlimited PTO
Federal Holiday Paid Leave
12 weeks of paid Parental Leave
Employer paid STD/LTD
Employer Paid Life Insurance
401K plan and Employer Match
Professional Development Assistance
Equity Incentive Plan

ATS Keywords

✓ Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonFastAPIasyncioPyTorchagent frameworksOpenAI Agents SDKgenerative AI modelsprompt engineeringLLM modelscloud-native architectures

Soft Skills

collaborationmentorshipcommunication