AI Senior Security Engineer

• Agentic Workflow Design: Build and maintain AI agents capable of multi-step reasoning and tool-use to automate cyber security use cases such as Autonomous Incident Investigation, vulnerability prioritization.
• Advanced Prompt Engineering with expertise in designing high-precision, version-controlled prompts with ability to programmatically optimize LLM outputs for reliable security logic and automated remediation scripts.
• Use and fine-tune machine learning models (like Deep Learning, K-MEANS, SVM etc) to identify sophisticated attack patterns that bypass traditional signature-based defenses.
• LLM Integration: Integrate large language models (OpenAI, Anthropic, or open-source models into production environments via APIs or local deployments.
• Data Pipeline Orchestration: Develop and optimize data ingestion pipelines, specifically focusing on Vector Databases
• Process Mapping & Optimization: Audit existing manual workflows and re-engineer them using a Machine-First mindset, utilizing LLMs to handle unstructured data.
• Infrastructure & MLOps: Deploy and monitor AI solutions using cloud-native tools, ensuring high availability, low latency, and cost-efficiency.
• Safety & Compliance: Implement guardrails for AI outputs to ensure ethical standards, data privacy, and Human-in-the-loop checkpoints where necessary.

vulnerability management api integration Docker & Kubernetes Security & Compliance Vector databases mlops Python LLM Integration

We’re seeking a highly motivated Security Engineer to design, develop, and deploy autonomous agents that eliminate manual overhead and drive intelligent decision-making across the organization while ensuring proper guardrails and security controls are implemented., * Experience in Python with hands-on in data ingestion, cleaning, machine learning libraries preferably in Scikit-Learn, Pytorch, system and web-based integrations.

• AI Frameworks: Proficiency with LangChain, CrewAI, or AutoGPT for agent orchestration.
• Machine Learning: Hands-on experience in using and tuning Machine Learning models for wide range of cyber security use cases.
• 3-4 years of hands-on experience with at least on the cloud AI solution (AWS Bedrock/SageMaker, Azure AI)
• DevOps: Docker, Kubernetes, and Git for version control and deployment.
• Deep experience with RESTful and GraphQL APIs to connect disparate systems.

Education:

• Bachelor’s or Masters degree in Cybersecurity, Computer Science, Artificial Intelligence or related field, or relevant industry certifications. Equivalent work experience is equally preferable.

Preferred Certifications:

• GIAC Machine Learning Engineer
• AWS Certified Machine Learning Engineer
• Microsoft Certified: Azure AI Engineer Associate
• Certified Information Systems Security Professional (CISSP)

The pay range that the employer in good faith reasonably expects to pay for this position is $36.06/hour - $56.34/hour. Our benefits include medical, dental, vision and retirement benefits. Applications will be accepted on an ongoing basis.