AI & Automation Engineer | Digital Forensics · DevSecOps & SRE · ML from Scratch | 100% Remote
Building deterministic multi-agent systems, hardened forensic engines, enterprise DevSecOps platforms, and neural algorithms from scratch — all production-grade, fully tested.
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🚀 Live Interactive Demo: huggingface.co/spaces/jmtheone/cibi-platform-hub (Full Screen Direct Access: jmtheone-cibi-platform-hub.static.hf.space)
Unified, enterprise-grade multi-agent orchestration and digital forensics workbench consolidating 4 flagship engines into a single reactive dashboard:
- 🔍 Forensic Lab: Multi-hypothesis LangGraph deduction DAG with AST SQL guardrails (#15) and ISO/IEC 27037 HMAC report sealing.
- 🛡️ Adversarial Range: 25 realistic OWASP LLM probes (LLM01-LLM10) with real-time guardrail bypass evaluation.
- ⚡ SRE Mission Control: Google SRE multi-window error budget burn rate curves and interactive Human-in-the-Loop (HITL #16) runbook dispatching.
- 🔬 DFIR Studio: Verifiable SHA-256 Merkle tree chain of custody & byte-level Shannon entropy inspection (
$H \in [0, 8.0]$ ).
| Repository | Scope | Modules | Highlights |
|---|---|---|---|
| digital-forensics-suite | Digital Forensics & DFIR | 6 | NetworkX crime graphs · Merkle-tree ISO/IEC 27037 custody · Shannon entropy file carving · Text-to-SQL forensic queries |
| devsecops-sre-toolkit | DevSecOps & SRE | 17 | CIS Benchmark hardening · Multi-window SLO burn-rate · Chaos fault injection · LangGraph self-healing code · OpenTelemetry tracing |
| ml-from-scratch-engine | ML Fundamentals | 6 | Autograd 34k evals/sec · Nano-Transformer · BPE 61k tokens/sec · HNSW VectorDB 982 QPS · MinHash 3.1k docs/sec |
| n8n-enterprise-automation-hub | Workflow Automation | 5 flows | OSINT enrichment · DevSecOps audit bridge · Forensic triage · SRE sentinel · RAG knowledge sync |
| Repository | Domain | Graph | Key Capabilities |
|---|---|---|---|
| langgraph-forensic-investigator | Forensic AI | 5 nodes | Hypothesis planning · AST anti-SQLi Text-to-SQL · k-way alibi timeline · HMAC-SHA256 ISO reports |
| langgraph-sre-incident-commander | SRE AI | 4 nodes | SLO burn-rate alerting · Log correlation · HITL remediation gates · Blameless postmortem generation |
| langgraph-adversarial-red-teamer | Security AI | 3 nodes | OWASP LLM Top 10 attack mutations · Guardrail resistance evaluation · Deterministic evasion/block classification |
Every repository enforces a 6-gate CI/CD pipeline (GitHub Actions):
🔐 Gitleaks (0 leaks) → 🛡️ Bandit SAST (0 findings) → 🔍 MyPy strict
→ 🧪 pytest ≥90% coverage → 📦 SBOM CycloneDX → 🚀 E2E demo / benchmarks
| Metric | Value |
|---|---|
| Integration tests passing | 225 / 225 (100%) |
| Average coverage | ≥ 95% |
| Bandit SAST findings | 0 |
| Gitleaks secrets detected | 0 |
| MyPy type errors | 0 |
| Repositories with CI | 7 / 7 |
| Total production packages | 34 |
languages = ["Python 3.11+"]
frameworks = ["LangGraph", "n8n", "Pydantic v2", "pytest", "NumPy"]
security = ["Bandit", "Gitleaks", "CycloneDX SBOM", "HMAC-SHA256", "CIS Benchmarks"]
infra = ["Docker", "GitHub Actions", "OpenTelemetry", "Prometheus", "SQLite"]
domains = ["Digital Forensics (DFIR)", "DevSecOps", "SRE", "ML from Scratch", "AI Agents"]Bridging Criminal Investigation & Criminology with hardened software engineering — applying investigative rigor to system design: deterministic behavior, cryptographic evidence integrity, zero-tolerance for security drift, and auditability at every layer.
100% Remote · Open to opportunities in AI Engineering, DevSecOps, Forensic Engineering & SRE