Senior Engineer — AI Security, Systems Engineering & Developer Productivity
Lead AI security and platform modernization initiatives across Digital Technology. Drive secure enterprise adoption of AI capabilities, establish an AI vulnerability-management and Mythos remediation roadmap, accelerate engineering modernization from legacy Java stacks to cloud-native platforms, and engineer rapid-release capabilities for emerging security threats.
Core Charter & Leadership
A hands-on Senior / Staff Engineer with minimum 10 years of systems engineering experience acting simultaneously as:
- Technical Leader: Mentoring platform engineers and setting standards for secure AI usage.
- Architect: Designing the end-to-end AI security posture, sandbox execution models, and modernization blueprints.
- Builder: Writing production-grade code, CI/CD gates, MCP servers, and custom remediation tooling.
Technical Skills Matrix
4 Key Pillars of Delivery
Master Modules & Topic Directory
Complete syllabus of all specialized engineering topics, architectures, and practice modules
GitHub Platform Ecosystem
Interactive SVG Architecture Hero: 6 interconnected pillars across IDE, Git Core, Actions CI/CD, GHAS, Codespaces, and Enterprise EMU.
GitHub Copilot Enterprise
Copilot Autofix, GHAS CodeQL integration, ZDR zero data retention, .copilotignore, and 3-stage validation gates.
Claude Skills & MCP Tooling
Structured YAML frontmatter, Model Context Protocol client-server architecture, and sandboxed developer workflows.
Agentic AI Architecture
12-Layer Production Blueprint: Runtime orchestrator, sub-agent delegation, LLM gateways, and threat real-world postmortems.
Enterprise AI Guardrails
Dual-Stage Defense: Input rails (Presidio + injection defense) & Output rails (hallucination, schema, Confused Deputy).
Dev Productivity & Telemetry
DORA 4-Key Metrics, SPACE framework, AITrendz.tech live case study, cycle time compression, and antipattern traps.
AI Security & LLM Defense
Interactive 7-layer AISecOps pipeline, complete OWASP Top 10 (2025), MITRE ATLAS matrix, and MCP tool sandboxing.
AI Sec Dev
Platform modernization, legacy friction trap vs golden paths, reachability CVE triage, and 3-tier flow metrics.
Mythos Remediation Roadmap
4-Phase vulnerability burndown strategy, EPSS prioritization, runtime reachability, and automated patch PRs.
Java & Systems Modernization
Java 8/11 → 21+ Virtual Threads, OpenRewrite automation, Kubernetes container hardening, and SLSA supply chains.
Senior & Staff Interview Q&As
Curated executive STAR scenario responses across AI governance, systems reliability, and platform engineering.
LLM & RAG Quick Ref
Golden one-liners, core enterprise acronyms decoded, and critical CLI commands for rapid reference.
Product AI Engineer
PE vs ProdSec vs Product AI Engineer matrix, the 6 core verticals with why-needed rationale, and high-frequency interview Q&As.
📅 30 - 60 - 90 Day Strategic Execution Blueprint
- Audit Shadow AI usage across Digital Technology using CASB/DNS logs.
- Establish GitHub Copilot Enterprise baseline and enforce `.copilotignore` boundaries.
- Catalog top 500 platform vulnerabilities in the Mythos pipeline.
- Baseline Java 8/11 inventory across core transactional services.
- Launch pilot of Copilot Autofix with GHAS & CodeQL on 20 critical repos.
- Build and deploy first enterprise Claude Skill with MCP for Jira & Git triage.
- Implement OpenRewrite automated recipes for Java 17/21 language features.
- Deploy Kyverno admission controllers on EKS to enforce signed container images.
- Scale Mythos remediation roadmap across all engineering tribes with EPSS scoring.
- Roll out automated Rapid Release Hotfix pipeline for sub-4-hour zero-day turnarounds.
- Instrument OpenTelemetry (OTel) metrics for developer velocity & LLM latency.
- Present board-level AI security posture report and measurable MTTR reduction.