Forward Deployed Engineer - AI SOC

AHEAD

29d • $160,000 - $200,000 • Hybrid

About The Position

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.

Requirements

• 5+ years of experience in security engineering, platform engineering, forward deployed engineering, solutions engineering, or related technical roles
• Hands-on experience implementing and operating modern SOC technologies such as SIEM, XDR, and SOAR
• Experience deploying cloud-native architectures on at least one major cloud provider such as AWS, Azure, or GCP
• Strong background in data integration, telemetry pipelines, normalization, and security analytics workflows
• Experience working directly with customers, internal stakeholders, or cross-functional delivery teams in implementation-focused environments
• Ability to lead technical engagements, drive execution, and influence outcomes without direct authority
• Strong understanding of security operations, detection and response, cloud security, identity security, and endpoint security
• Experience with scripting and automation using tools such as Python, PowerShell, or Bash
• Familiarity with APIs and integration patterns including REST, webhooks, and event-driven workflows
• Working knowledge of AI and ML concepts relevant to SOC use cases, including anomaly detection, behavior analytics, LLMs, vector search, and AI assistants

Nice To Haves

• Experience with security data and analytics platforms such as Kafka, Kinesis, Pub/Sub, Spark, Databricks, BigQuery, Snowflake, or similar technologies is a plus
• Strong problem-solving skills, execution mindset, and ability to operate effectively in ambiguous, fast-moving environments
• Experience in MSSP, MDR, XDR, or other security service delivery environments
• Experience deploying solutions in regulated or compliance-sensitive environments
• Familiarity with infrastructure as code, CI/CD workflows, and production software delivery practices
• Experience building reusable implementation frameworks or field engineering playbooks
• Relevant certifications are a plus, including cloud, security, or platform-specific certifications

Responsibilities

• Serve as the technical lead for deploying and operationalizing security and AI solutions in customer or enterprise environments
• Translate business, operational, and security requirements into deployable architectures and implementation plans
• Partner with internal and external stakeholders to ensure solutions are aligned to operational goals, compliance requirements, and long-term platform strategy
• Act as a trusted advisor during onboarding, implementation, rollout, and optimization phases
• Design and implement integrations across SIEM, XDR, SOAR, case management, data platforms, and AI-enabled tooling
• Build and configure cloud-native data ingestion, normalization, and enrichment pipelines for security telemetry
• Integrate APIs, webhooks, message queues, and automation workflows across identity, endpoint, cloud, network, and application ecosystems
• Develop reusable deployment patterns, templates, and technical assets to accelerate future implementations
• Operationalize AI and automation use cases within security workflows, including alert enrichment, triage support, summarization, clustering, playbook selection, and analyst copilots
• Work with detection engineering and data teams to support implementation of behavioral analytics, anomaly detection, risk scoring, and other AI-assisted security use cases
• Help define data requirements, feedback loops, and operational guardrails needed to support effective AI outcomes in production environments
• Ensure deployed solutions are practical, measurable, and aligned to analyst workflows and response objectives
• Implement secure and governed automation for investigation and response use cases across heterogeneous environments
• Support resiliency, observability, performance, and scale requirements for deployed solutions
• Troubleshoot integration issues, deployment blockers, and production challenges in partnership with platform, cloud, and security teams
• Improve reliability and maintainability through documentation, testing, monitoring, and standardized engineering practices
• Collaborate across Security Operations, Security Engineering, Detection Engineering, Data Science, Infrastructure, and product or customer teams
• Communicate technical concepts clearly to both technical and non-technical stakeholders
• Mentor engineers and contribute to best practices for implementation, delivery, and technical solution design
• Provide field feedback to influence platform roadmap, product direction, and architectural standards

Benefits

• Medical, Dental, and Vision Insurance
• 401(k)
• Paid company holidays
• Paid time off
• Paid parental and caregiver leave

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Associate degree