Agentic Workflow Engineer

Job Title: Agentic Workflow Engineer (Cybersecurity)Type of Engagement: ContractLocation: Juno Beach, FLResponsibilities:Design, develop, and deploy AI-powered agentic workflows to automate cybersecurity operations.Build production-grade AI agents using Python, LLMs, RAG, and orchestration frameworks such as LangChain, LangGraph, CrewAI, or similar.Develop multi-step reasoning workflows that leverage AI agents capable of using enterprise tools and APIs.Integrate AI solutions with cybersecurity platforms including SIEM, SOAR, EDR, IAM, ticketing systems, and other internal security tools.Build Retrieval-Augmented Generation (RAG) pipelines using enterprise security documentation, playbooks, and knowledge bases.Develop secure APIs and integrate AI agents using Model Context Protocol (MCP) or standard REST APIs.Collaborate with Threat Hunting, Incident Response, Vulnerability Management, IAM, Compliance, and Security Operations teams to automate security workflows.Deploy, monitor, and optimize AI applications on AWS, including Amazon Bedrock or similar Generative AI platforms.Ensure AI workflows meet enterprise standards for security, governance, auditability, logging, and compliance.Perform LLM testing, evaluation, prompt optimization, and production support for scalable AI solutions.Required Skills:Strong hands-on experience with Python, including production-quality development, testing, packaging, and API development.Experience building Agentic AI applications using LangChain, LangGraph, CrewAI, AutoGen, OpenAI Agents SDK, or similar frameworks.Strong understanding of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering, tool/function calling, and multi-agent workflows.Experience integrating AI applications with enterprise APIs and external tools.Working knowledge of cybersecurity concepts including Threat Hunting, Incident Response, SIEM, SOAR, EDR, IAM, Vulnerability Management, and Compliance.Experience with AWS services, especially Amazon Bedrock or other cloud-based Generative AI platforms.Knowledge of secure software development, secrets management, logging, monitoring, and enterprise governance.Strong understanding of scalable system design and deploying AI applications into production environments.Excellent problem-solving, communication, and cross-functional collaboration skills.Preferred Skills:Experience integrating with Splunk, Microsoft Sentinel, QRadar, CrowdStrike, SentinelOne, Cortex XSOAR, ServiceNow, Jira, or similar security platforms.Experience with Model Context Protocol (MCP).Hands-on experience evaluating LLM performance, hallucination testing, prompt evaluation, and AI quality metrics.Experience with Vector Databases such as Pinecone, FAISS, Weaviate, ChromaDB, or Milvus.Familiarity with Docker, Kubernetes, CI/CD pipelines, and enterprise cloud deployments.Experience building secure, compliant AI applications within regulated enterprise environments.Additional Information:Strong experience in Python, Generative AI, Agentic AI, LLMs, RAG, LangChain/LangGraph/CrewAI, AWS, and Cybersecurity Automation is required.Candidates with experience building production-ready AI agents, integrating enterprise security tools (SIEM/SOAR/EDR), automating SOC workflows, and deploying secure AI solutions in regulated environments are highly preferred.