Title: Sr Solution Architect (AI / Cybersecurity)
Location: Irving, TX
Duration: Long-term
Onsite position
Responsibilities:
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.
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).
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.
Required Qualifications:
· Experience: 10+ years of progressive experience in Cloud and Software Architecture.
· AWS Mastery: Deep, demonstrable expertise in AWS networking, compute (ECS/Fargate), and serverless data stores (DynamoDB, OpenSearch, API Gateway, Lambda) [cite: 3]. AWS Solutions Architect Professional certification is highly preferred.
· Generative AI: Hands-on 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.
· Security Acumen: Ability to understand complex enterprise encryption standards (TLS, IPsec, AES-256) and how they translate to infrastructure configurations.
