Cybersecurity Contractor: 6-9 years (Advanced)

Job Description

Job Description

Job Description: Full Stack AI Lead – AI Agents & Cybersecurity Automation
Location: Remote (approximately 10% travel may be required)
Role Title: Full Stack AI Lead

Job Summary
We are seeking an experienced Full Stack AI Lead to drive the architecture, design, and development of AI-enabled applications, intelligent agents, APIs, dashboards, integrations, and cybersecurity automation solutions across the S&P Flywheel.
This role requires strong hands-on technical leadership across frontend and backend development, AI agent orchestration, distributed systems, and enterprise security integrations. The ideal candidate will have deep expertise in TypeScript, Vue.js 3 or React/Next.js, Python, FastAPI, asynchronous programming, Go microservices, and agentic AI frameworks such as LangGraph.
The successful candidate will lead engineering efforts across Prepare, Scan, Remediation, and Monitor pods, establish engineering standards, mentor developers, resolve complex technical challenges, and deliver secure, scalable, production-ready AI solutions. Strong experience building AI agents capable of executing tools and actions in real-world workflows, along with an understanding of cybersecurity platforms and processes, is essential.
Key Responsibilities
Full-Stack Development and Technical Leadership

• Lead the design and development of AI-powered applications, agents, APIs, dashboards, integrations, and cybersecurity automation solutions.
• Provide hands-on technical leadership across Prepare, Scan, Remediation, and Monitor pods, coordinating frontend, backend, AI orchestration, integration, processing, and platform dependencies.
• Lead frontend development using TypeScript and Vue.js 3 (preferred), or React/Next.js, to build real-time interfaces, vulnerability graphs, approval workflows, code-diff experiences, data-intensive dashboards, and executive reporting capabilities.
• Establish reusable frontend components, API contracts, coding standards, and engineering best practices to ensure maintainable and reliable applications.

Backend Engineering and Distributed Systems

• Lead the development of backend services and microservices using Python, FastAPI, asyncio, and Go.
• Design resilient APIs and connectors with robust authentication, rate limiting, retries, idempotency, and event-driven processing.
• Build and maintain distributed, data-intensive systems with a focus on concurrency, reliability, performance, and scalability.
• Ensure effective integration between frontend applications, backend services, AI components, and enterprise platforms.

AI Agents and LLM Orchestration

• Design and implement agentic AI solutions using LangGraph or custom agent-loop architectures.
• Implement LLM function calling, structured outputs, tool execution, and model-agnostic gateways to support enterprise AI workflows.
• Establish evaluation frameworks, guardrails, server-side approval mechanisms, and tracing and observability capabilities for AI agents.
• Develop AI agents capable of executing tools and actions within controlled workflows, beyond basic chatbot and retrieval-augmented generation (RAG) implementations.
• Ensure AI-enabled applications follow appropriate security, validation, governance, and human-approval practices.

Cybersecurity Integrations and Automation

• Lead integrations with enterprise cybersecurity and development platforms, including SIEM systems, Wiz, Tenable, Qualys, Checkmarx, GitHub, Jira, ServiceNow, cloud platforms, CI/CD systems, and IAM solutions.
• Develop automation workflows that support vulnerability scanning, remediation, monitoring, approvals, and security operations.
• Collaborate with cybersecurity domain experts to translate security requirements into reliable application features and automated workflows.

Engineering Standards and Production Readiness

• Establish standards for secure coding, API design, code reviews, automated testing, telemetry, performance optimization, scalability, deployment, and production readiness.
• Drive reliability and operational excellence across application services, integrations, and AI orchestration components.
• Troubleshoot complex technical issues, remove engineering blockers, and support production operations and continuous improvement.
• Ensure adequate observability, error handling, and operational controls across distributed services and AI-enabled workflows.

Collaboration and Team Leadership

• Mentor engineers and provide technical guidance across frontend, backend, and AI engineering teams.
• Partner with Architecture, Security Domain, Site Reliability Engineering (SRE), Quality Assurance (QA), and client stakeholders to align technical solutions with business and security requirements.
• Support technical demonstrations, architecture discussions, implementation documentation, and knowledge-sharing activities.
• Coordinate dependencies across engineering teams to ensure timely delivery of secure, scalable, and maintainable solutions.

Required Qualifications

• Strong experience leading the design, development, and production ownership of full-stack applications and distributed, data-intensive systems.
• Advanced proficiency in TypeScript and Vue.js 3, preferably, or React/Next.js.
• Strong backend development experience using Python, FastAPI, and asyncio, with experience in Go microservices.
• Deep understanding of asynchronous programming, concurrency, event-driven architectures, API design, and distributed systems.
• Hands-on experience implementing AI agents using LangGraph or custom agent-loop architectures.
• Practical experience with LLM function calling, structured outputs, agent tool execution, evaluation, guardrails, and tracing or observability.
• Experience integrating enterprise platforms, APIs, security tools, cloud services, CI/CD pipelines, and IAM systems.
• Strong understanding of cybersecurity concepts, vulnerability management, security operations, and remediation workflows.
• Experience establishing secure coding practices, automated testing, code review standards, monitoring, and production-readiness processes.
• Proven ability to lead technical delivery, mentor engineers, troubleshoot complex issues, and collaborate with cross-functional teams.
• Strong communication, analytical, and problem-solving skills.

Preferred Qualifications

• Experience with Vue.js 3 and modern TypeScript-based frontend architectures.
• Experience with LangGraph, custom AI agent orchestration, and model-agnostic LLM integration patterns.
• Familiarity with SIEM, Wiz, Tenable, Qualys, Checkmarx, GitHub, Jira, ServiceNow, and enterprise IAM platforms.
• Experience building cybersecurity automation solutions for vulnerability scanning, remediation, and monitoring.
• Experience operating production AI systems with robust observability, evaluation, security controls, and human-in-the-loop approvals.
• Experience coordinating engineering delivery across multiple teams or workstreams.

Ideal Candidate Profile
The ideal candidate is a hands-on technical leader who combines full-stack engineering expertise, production-grade distributed systems experience, and advanced agentic AI implementation skills. They should be capable of leading engineers while remaining deeply involved in architecture, coding, integration, troubleshooting, and deployment.
Candidates must demonstrate practical experience building AI agents that execute tools and actions, strong asynchronous and concurrency programming skills, ownership of production systems, and a solid understanding of cybersecurity workflows.
Work Arrangement: Remote, with approximately 10% travel potentially required.