Artificial Intelligence Engineer

Job Title: AI Engineer (LLM & Agentic Systems – Data Platform / Security Hub) Remote Long term contract(W2) Role Overview Apex Systems is seeking an AI Engineer to design and implement AI-enabled capabilities within a large-scale Data Platform and Security Hub solution. This role focuses on delivering LLM-driven automation, agent-based workflows, and intelligent orchestration to enhance security operations, improve efficiency, and reduce manual intervention across an enterprise data environment. The engineer will play a key role in embedding AI into real-time systems that support issue triage, remediation, and operational decision-making. Key Responsibilities • Design and implement LLM-powered workflows to support security operations, including intelligent issue triage, classification, and remediation assistance • Develop and deploy agent-based automation frameworks using tools such as LangGraph (or similar orchestration frameworks) to enable multi-step reasoning and workflow execution • Integrate AI capabilities into event-driven and real-time systems supporting security, compliance, and data governance processes • Enable AI-assisted CI/CD and operational workflows, including automated quality checks, release processes, and decision support • Collaborate with backend, data, and DevOps teams to embed AI into platform services and ensure seamless integration with existing pipelines and systems • Support automation of security lifecycle processes, including alerting, escalation, and audit workflows Required Qualifications (Must-Haves) • Hands-on experience building AI/ML or LLM-based solutions, including implementation of agent-based or multi-step reasoning systems • Experience developing AI-driven workflow automation, such as intelligent issue triage, orchestration, or decisioning systems in operational environments • Strong understanding of LLM frameworks and orchestration tools, including exposure to LangGraph, LangChain, or similar agent orchestration libraries • Experience working with large-scale, real-time or event-driven systems, supporting high-volume data processing and integration into enterprise platforms • Strong software engineering fundamentals, with the ability to build and integrate scalable AI components into production systems Preferred Qualifications (Nice-to-Haves) • Proficiency in Python for AI and backend integration use cases (directly aligned to project’s Python-based architecture) • Experience with AI-assisted CI/CD, agentic automation, or bot-driven workflows • Familiarity with security or compliance platforms, including vulnerability management or governance workflows • Experience integrating AI into data platforms or pipeline environments • Exposure to distributed systems and microservices architectures Technical Environment • AI & Orchestration: LLMs, LangGraph / LangChain (agent-based frameworks) • Platform: Containerized, on-prem Data Platform • Architecture: Event-driven, real-time processing • Focus Areas: AI-assisted automation, workflow orchestration, intelligent issue management • Integration: Backend services, data pipelines, and DevOps workflows