Sr Solution Architect (AI / Cybersecurity)

Role Sr Solution Architect (AI / Cybersecurity)
Location Irving, TX (Hybrid)

Experience: 10+ years of progressive experience in Solution Architect (AI / Cybersecurity)

AWS Mastery: Deep, demonstrable expertise in AWS networking, compute (ECS/Fargate), and serverless data stores (DynamoDB, OpenSearch, API Gateway, Lambda)

AWS Solutions Architect Professional certification

Generative AI: Architectural experience with Generative AI orchestration frameworks (LangGraph, LangChain) and LLM APIs (Amazon Bedrock, Claude, Gemini).

DevSecOps: Strong foundation in DevSecOps practices, Infrastructure-as-Code (Terraform), and automated remediation pipelines.
Senior Solution Architect to lead the technical design and execution of a strategic, AI-driven cybersecurity initiative.

• Operating initially within an isolated InfoVision AWS Sandbox before scaling to enterprise production, you will be the definitive technical authority driving this initiative.
• You will architect the multi-agent orchestration pipeline, integrate Large Language Models (LLMs), and ensure the seamless translation of enterprise security rules into executable Infrastructure-as-Code (IaC) templates.
• role requires a hands-on architectural leader who can bridge the gap between DevSecOps, Cloud Infrastructure, and Generative AI to deliver a scalable, long-term solution.

Day-to-Day Responsibilities

1. AI & Agentic Orchestration Architecture

• Design the Agent Pipeline: Architect the cyclic graph state machines using LangGraph on AWS ECS Fargate, defining the exact hand-offs between the Scan, Classify, Plan, and Execute agents.
• LLM Integration: Oversee the integration of Amazon Bedrock (Claude/Gemini APIs), designing the prompt structures and context-handling logic required to parse complex Software Bill of Materials (SBOM) and Cryptography Bill of Materials (CBOM) outputs.
• RAG Implementation: Architect a Retrieval-Augmented Generation (RAG) vector system using OpenSearch to dynamically map scan findings against the established North Star rule dictionary.

2. Cloud Infrastructure & Security Design

• Infrastructure Architecture: Design and govern the secure AWS environment (VPC, IAM, CloudWatch) to initially isolate the development sandbox and eventually scale into production pipelines.
• State & Approval Management: Architect the state-management layer using DynamoDB to track remediation checkpoints [cite: 3]. Design the "Reviewer Dashboard" using API Gateway, AWS Lambda, and Amazon Cognito to enforce human-in-the-loop approval gates.
• CI/CD & DevOps Integration: Oversee the offshore AWS Cloud/DevOps engineers building the automated execution pipelines (AWS CodeBuild, SSM, Git PR automation).

3. Technical Strategy & Template Governance

• Rule-to-Template Mapping: Own the baseline mapping table. Translate the characteristic maps (provided by the on-site data analysis team) into the logical frameworks required for the IaC remediation templates.
• Vulnerability Simulation & Testing: Guide the engineering team on how to accurately inject industry-standard cryptographic vulnerabilities (e.g., TLS 1.2, AES-128, hardcoded secrets) into reference applications to simulate real-world conditions during the initial build phase.
• Cross-Functional Technical Alignment: Act as the technical bridge between the on-site secure analysis teams and the offshore AI engineering teams, ensuring the AI agents are being built to solve the correct enterprise constraints.