Job description

Ampcus Inc. is a certified global provider of a broad range of Technology and Business consulting services. We are in search of a highly motivated candidate to join our talented Team. Job Title: AI Senior Security Engineer Location(s): Jersey City, NJ, Tampa, FL or Phoenix AZ Job Summary Seeking a highly motivated Security Engineer to design, develop, and deploy autonomous AI agents that reduce manual overhead and drive intelligent decision-making across cybersecurity operations while ensuring appropriate guardrails, security controls, data privacy, and human oversight. Key Responsibilities • Design, build, and maintain AI agents capable of multi-step reasoning and tool use to automate cybersecurity use cases, including autonomous incident investigation and vulnerability prioritization. • Develop advanced prompt engineering solutions using high-precision, version-controlled prompts and programmatic techniques to optimize LLM outputs for reliable security logic and automated remediation. • Use and fine-tune machine learning models, including deep learning, K-Means, SVM, and related techniques, to identify sophisticated attack patterns that bypass traditional signature-based defenses. • Integrate large language models from providers such as OpenAI, Anthropic, and open-source platforms into production environments through APIs or local deployments. • Develop and optimize data ingestion pipelines, with a particular focus on vector databases and AI-ready data processing. • Audit existing manual workflows and re-engineer them using a machine-first approach, leveraging LLMs to process and analyze unstructured data. • Deploy, monitor, and optimize AI solutions using cloud-native technologies, ensuring high availability, low latency, scalability, and cost efficiency. • Implement AI safety and security guardrails to ensure appropriate outputs, ethical standards, data privacy, and human-in-the-loop checkpoints where required. Required Qualifications • Hands-on experience with Python, including data ingestion, data cleaning, machine learning libraries, and system and web-based integrations. • Proficiency with machine learning frameworks and libraries, preferably Scikit-Learn and PyTorch. • Experience with AI agent orchestration frameworks such as LangChain, CrewAI, or AutoGPT. • Hands-on experience developing and tuning machine learning models for a range of cybersecurity use cases. • 3–4 years of hands-on experience with at least one cloud-based AI platform, such as AWS Bedrock, AWS SageMaker, or Azure AI. • Experience with Docker, Kubernetes, and Git for deployment and version control. • Strong experience with RESTful and GraphQL APIs for integrating disparate systems. • Experience designing and implementing AI/ML solutions in cybersecurity environments. Education • Bachelor's or Master's degree in Cybersecurity, Computer Science, Artificial Intelligence, or a related field. • Relevant industry certifications and equivalent practical work experience may be considered. Preferred Certifications • GIAC Machine Learning Engineer • AWS Certified Machine Learning Engineer • Microsoft Certified: Azure AI Engineer Associate • Certified Information Systems Security Professional (CISSP) Ampcus is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veterans or individuals with disabilities.

Requirements

Must-haves

Ampcus Inc. is a certified global provider of a broad range of Technology and Business consulting services. We are in search of a highly motivated candidate to join our talented Team.
Job Title: AI Senior Security Engineer
Location(s): Jersey City, NJ, Tampa, FL or Phoenix AZ
Design, build, and maintain AI agents capable of multi-step reasoning and tool use to automate cybersecurity use cases, including autonomous incident investigation and vulnerability prioritization.
Develop advanced prompt engineering solutions using high-precision, version-controlled prompts and programmatic techniques to optimize LLM outputs for reliable security logic and automated remediation.
Use and fine-tune machine learning models, including deep learning, K-Means, SVM, and related techniques, to identify sophisticated attack patterns that bypass traditional signature-based defenses.
Integrate large language models from providers such as OpenAI, Anthropic, and open-source platforms into production environments through APIs or local deployments.
Develop and optimize data ingestion pipelines, with a particular focus on vector databases and AI-ready data processing.
Audit existing manual workflows and re-engineer them using a machine-first approach, leveraging LLMs to process and analyze unstructured data.
Deploy, monitor, and optimize AI solutions using cloud-native technologies, ensuring high availability, low latency, scalability, and cost efficiency.
Implement AI safety and security guardrails to ensure appropriate outputs, ethical standards, data privacy, and human-in-the-loop checkpoints where required.
Hands-on experience with Python, including data ingestion, data cleaning, machine learning libraries, and system and web-based integrations.
Proficiency with machine learning frameworks and libraries, preferably Scikit-Learn and PyTorch.
Experience with AI agent orchestration frameworks such as LangChain, CrewAI, or AutoGPT.
Hands-on experience developing and tuning machine learning models for a range of cybersecurity use cases.
3–4 years of hands-on experience with at least one cloud-based AI platform, such as AWS Bedrock, AWS SageMaker, or Azure AI.
Experience with Docker, Kubernetes, and Git for deployment and version control.
Strong experience with RESTful and GraphQL APIs for integrating disparate systems.
Experience designing and implementing AI/ML solutions in cybersecurity environments.
Bachelor's or Master's degree in Cybersecurity, Computer Science, Artificial Intelligence, or a related field.
Relevant industry certifications and equivalent practical work experience may be considered.
GIAC Machine Learning Engineer
AWS Certified Machine Learning Engineer

Nice-to-haves

Preferred Certifications

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aillmmachine learningpythonawsazuredockerkubernetesgraphqlml

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