Appian Corporation

Appian Corporation

Lead AI Security Engineer

McLean, Virginia · Mid

Sponsorship not specified$150k-$275kDetected 6 days ago
PythonAlgorithmsVector DatabasesAWSGCPAzureCloud PlatformsKubernetesRESTMachine LearningLLMsRAGAgentic AICybersecuritySIEMMicrosoft SentinelSOC OperationsIncident ResponseRecruitingElectrical EngineeringResearchMentoringAdaptability

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odds of building a lasting career here

61Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role90
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70

Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.

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Employer immigration record

from this employer's Department of Labor filings

Green-card filing pattern in this occupation

Context, not a finding about this posting: of this employer's 5 green-card filings in this occupation, 100% were for a worker who already held the job.

Files H-1B transfers

2 transfer filings in the last year, covering 2 workers. Median labor-condition decision: 32 days. An employer that already files transfers is one that can take over an existing H-1B.

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About the role

  • Our mission is to move beyond reactive alerting by creating self-orchestrating, context-aware AI systems capable of autonomous triage, semantic correlation, and proactive threat mitigation.
  • In this role, you will leverage emerging AI capabilities to reimagine how we defend our organization.
  • The AI SOC Engineering team is at the center of bringing our vision for AI-driven security to This is a squad of builders operating at the intersection of Generative AI, software engineering, and offensive/defensive security.

Responsibilities

  • Build & Deploy Agents: Design, test, and deploy autonomous and semi-autonomous AI agents that integrate natively with our enterprise security stack (SIEM, EDR, XDR, and Threat Intel feeds).
  • Optimize RAG Pipelines: Design, optimize, and maintain production-grade Retrieval-Augmented Generation (RAG) workflows to inject real-time security context, network topology, and historical incident logs into agent prompts.
  • LLM Performance Engineering: Continuously evaluate, benchmark, and optimize LLM performance, context window utilization, latency, and cost-efficiency across various models (OSS and commercial).
  • Design Human-in-the-Loop (HITL): Collaborate deeply with Tier 3 Analysts and Threat Hunters to engineer seamless HITL handoff mechanisms, ensuring agents safely escalate complex anomalies to humans.
  • Secure the AI: Implement robust security boundaries around our LLM architecture, mitigating risks like prompt injection, data poisoning, model tool-abuse, and addressing the OWASP Top 10 for LLMs.
  • Build & Deploy Agents:
  • Design, test, and deploy autonomous and semi-autonomous AI agents that integrate natively with our enterprise security stack (SIEM, EDR, XDR, and Threat Intel feeds).
  • Optimize RAG Pipelines:
  • Design, optimize, and maintain production-grade Retrieval-Augmented Generation (RAG) workflows to inject real-time security context, network topology, and historical incident logs into agent prompts.
  • Continuously evaluate, benchmark, and optimize LLM performance, context window utilization, latency, and cost-efficiency across various models (OSS and commercial).

Requirements

  • 5+ years of experience programming with Python
  • 2+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g., AWS, Google Cloud, Azure)
  • Resilient: You are a trailblazer who can forge new paths to achieve security goals in an evolving threat landscape.

Nice to have

  • Proven experience working with production Vector Databases (e.g., Pinecone, Qdrant, Milvus, or Weaviate ) for semantic chunking, embedding generation, and metadata filtering.
  • Experience interfacing with cybersecurity platforms via REST APIs/Webhooks (e.g., Splunk, CrowdStrike, Microsoft Sentinel, Palo Alto XSOAR).
  • Experience deploying and scaling AI workloads in containerized cloud environments (AWS, Azure, or GCP using Kubernetes/EKS/AKS)
  • Understanding of fine-tuning methodologies (LoRA, QLoRA) for smaller, domain-specific open-source models (e.g., Llama 3, Mistral) tailored for security log analysis
  • Passion for staying abreast of the latest AI research and security systems, and an ability to judiciously apply novel techniques in production.

Compensation

  • $150,000 - $275,000 USD

Benefits

  • Appian offers a comprehensive benefits package designed to support your health, wellbeing, and financial future.
  • Benefits vary by country-please ask your Talent Acquisition contact for details specific to the location you are applying to.

Company info

  • Here at Appian, our values of Intensity and Excellence define who we are.
  • We set high standards and live up to them, ensuring that everything we do is done with care and quality.
  • We approach every challenge with ambition and commitment, holding ourselves and each other accountable to achieve the best results.
  • When you join Appian, you'll be part of a passionate team dedicated to accomplishing hard things, together.
  • Lead AI Security Engineer (Agentic SOC)
  • McLean/Tysons, VA | On-site (5 days/week)
  • We are pioneering the next generation of cyber defense by building an Agentic Security Operations Center (SOC).
  • We don't just write scripts; we architect the intelligent fabric of our defensive posture.
  • We build and deploy production-grade, proprietary multi-agent systems that empower our human analysts to handle complex incident response with autonomous agents AI in responsible and scalable ways.

Equal opportunity

  • equal opportunity employer that strives to attract and retain the best talent.
  • If you need a reasonable accommodation for any part of the employment process, please contact us by email at ReasonableAccommodations@appian.com.
  • Please note that only inquiries concerning a request for reasonable accommodation will be responded to from this email address.

This listing is sourced directly from Appian Corporation's careers page and normalized into a canonical job model.