Forward Deployed Engineer - AI SOC
The Forward Deployed Engineer is responsible for deploying, integrating, and operationalizing next-generation security and AI capabilities in real-world customer and enterprise environments. This role works at the intersection of engineering, security operations, data, and customer success to translate complex requirements into scalable, production-ready solutions.
This individual partners closely with security leaders, analysts, platform teams, data scientists, and infrastructure stakeholders to implement AI-enabled SOC workflows, integrate security tooling, improve analyst experience, and accelerate time to value. The ideal candidate combines strong hands-on engineering skills with a deep understanding of SOC operations, cloud platforms, automation, and customer-facing delivery.
Responsibilities:
Serve as the technical lead for deploying and operationalizing security and AI solutions in customer or enterprise environmentsTranslate business, operational, and security requirements into deployable architectures and implementation plansPartner with internal and external stakeholders to ensure solutions are aligned to operational goals, compliance requirements, and long-term platform strategyAct as a trusted advisor during onboarding, implementation, rollout, and optimization phasesDesign and implement integrations across SIEM, XDR, SOAR, case management, data platforms, and AI-enabled toolingBuild and configure cloud-native data ingestion, normalization, and enrichment pipelines for security telemetryIntegrate APIs, webhooks, message queues, and automation workflows across identity, endpoint, cloud, network, and application ecosystemsDevelop reusable deployment patterns, templates, and technical assets to accelerate future implementationsOperationalize AI and automation use cases within security workflows, including alert enrichment, triage support, summarization, clustering, playbook selection, and analyst copilotsWork with detection engineering and data teams to support implementation of behavioral analytics, anomaly detection, risk scoring, and other AI-assisted security use casesHelp define data requirements, feedback loops, and operational guardrails needed to support effective AI outcomes in production environmentsEnsure deployed solutions are practical, measurable, and aligned to analyst workflows and response objectivesImplement secure and governed automation for investigation and response use cases across heterogeneous environmentsSupport resiliency, observability, performance, and scale requirements for deployed solutionsTroubleshoot integration issues, deployment blockers, and production challenges in partnership with platform, cloud, and security teamsImprove reliability and maintainability through documentation, testing, monitoring, and standardized engineering practicesCollaborate across Security Operations, Security Engineering, Detection Engineering, Data Science, Infrastructure, and product or customer teamsCommunicate technical concepts clearly to both technical and non-technical stakeholdersMentor engineers and contribute to best practices for implementation, delivery, and technical solution designProvide field feedback to influence platform roadmap, product direction, and architectural standardsRequired Qualifications 5+ years of experience in security engineering, platform engineering, forward deployed engineering, solutions engineering, or related technical rolesHands-on experience implementing and operating modern SOC technologies such as SIEM, XDR, and SOARExperience deploying cloud-native architectures on at least one major cloud provider such as AWS, Azure, or GCPStrong background in data integration, telemetry pipelines, normalization, and security analytics workflowsExperience working directly with customers, internal stakeholders, or cross-functional delivery teams in implementation-focused environmentsAbility to lead technical engagements, drive execution, and influence outcomes without direct authorityTechnical SkillsStrong understanding of security operations, detection and response, cloud security, identity security, and endpoint securityExperience with scripting and automation using tools such as Python, PowerShell, or BashFamiliarity with APIs and integration patterns including REST, webhooks, and event-driven workflowsWorking knowledge of AI and ML concepts relevant to SOC use cases, including anomaly detection, behavior analytics, LLMs, vector search, and AI assistantsExperience with security data and analytics platforms such as Kafka, Kinesis, Pub/Sub, Spark, Databricks, BigQuery, Snowflake, or similar technologies is a plusStrong problem-solving skills, execution mindset, and ability to operate effectively in ambiguous, fast-moving environmentsPreferred QualificationsExperience in MSSP, MDR, XDR, or other security service delivery environmentsExperience deploying solutions in regulated or compliance-sensitive environmentsFamiliarity with infrastructure as code, CI/CD workflows, and production software delivery practicesExperience building reusable implementation frameworks or field engineering playbooksRelevant certifications are a plus, including cloud, security, or platform-specific certificationsEducationBachelor’s degree in Computer Science, Information Security, Engineering, or equivalent practical experience