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Remote: Yes (100% Remote only)

Willing to relocate: No

Role: AI Systems Architect | Human-AI Tandem Operator (System Topology, Specification & Logic Design)

Technologies: LLM Context Architecture, Invariant Modeling, Deterministic Serialization, State-Machine Orchestration, Inference Forensics (Target runtimes: Python, Rust, vLLM, llama.cpp)

Résumé/CV: https://github.com/Recursive-Logic-Core (Full CV upon request via email)

Email: [email protected]

I operate strictly as a calibrated Human-AI Tandem at the structural and invariant level: AI engines handle syntax generation, code implementation, and blind reverse-auditing, while I direct system topology, causal logic, and boundary verification against the 7 core transformer failure modes:

1. Lost-in-the-Middle (Attention Decay)

2. Stochastic Drift (Absent State Invariance)

3. Confidence-Accuracy Decoupling (Hallucinations)

4. Context Window Saturation (State Loss)

5. Needle-in-a-Haystack (Retrieval Failure)

6. Sycophancy (RLHF Alignment Bias)

7. Control-Data Conflation (Prompt Injection)

Key Artifacts & Open-Source Forensics:

- SLAP: Deterministic, bracketless tree serialization in O(N) single-pass (>50% token payload reduction vs. JSON) -> https://github.com/Recursive-Logic-Core/SLAP

- DriftBreak: Local context governor mitigating state and context drift on localhost -> https://github.com/Recursive-Logic-Core/DriftBreak

- Context Architecture: Structural mitigation frameworks for all 7 LLM failure modes -> https://github.com/Recursive-Logic-Core/llm-context-architec...

- System Forensics: Public root-cause isolation in production runtimes (vLLM & llama.cpp: recurrent state drift, ROCm/CUDA memory fragmentation, FSM token loops) -> https://github.com/Recursive-Logic-Core/system-analysis

Terms: Full-time employment (German contract or via Employer of Record / EoR)

Languages: German (native), English (fluent written, async-first)

Notice Period: 2 months to end of month

Remote: Yes (100% Remote only)

Willing to relocate: No

Technologies: LLM Context Architecture, System Topology, Invariant Modeling, Deterministic Serialization, Logic Orchestration, State Recovery (Target stacks for AI: Python, Rust, JSON, etc.)

GitHub: https://github.com/Recursive-Logic-Core

Résumé/CV: Available upon request via email

Role: AI Systems Architect (System Topology, Specification & Logic Design)

Focus: Eliminating LLM failure modes (context rot, attention drift). I operate purely at the architectural and logic-orchestration level (I do not write manual syntax/code; AI generates implementation while I audit logic).

Projects: - SLAP: https://github.com/Recursive-Logic-Core/SLAP - DriftBreak: https://github.com/Recursive-Logic-Core/DriftBreak - Context: https://github.com/Recursive-Logic-Core/llm-context-architec... - Forensics: https://github.com/Recursive-Logic-Core/system-analysis

Terms: German employment contract & benefits (EoR welcome)

Languages: German (native), English (fluent written, async-first)

Notice Period: 2 months to end of month

Email: [email protected]

Remote: Yes (100% Remote only)

Willing to relocate: No

Technologies: LLM Context Architecture, Deterministic Serialization Protocols, Localhost Session Governance, State/Glossary Recovery, System Analysis, Logic Orchestration, Unstructured Data Forensics

GitHub Profile: https://github.com/Recursive-Logic-Core

Résumé/CV: Available upon request via email

Role: AI Systems Analyst & Architect (Concept & Orchestration)

Focus: Designing structural logic frameworks, context architectures, and deterministic control layers to solve core LLM limitations (Context Rot, Lost-in-the-Middle, hallucination loops, Attention Drift). I build fast, AI-orchestrated architectural prototypes and proof-of-concept tools across any tech stack to validate system logic - focusing on high-efficiency architecture, state mechanics, and system design rather than manual syntax-grinding for legacy codebases.

Key Deliverables & Implementations:

- SLAP Protocol (v1.0.0): Deterministic, zero-overhead context serialization & line-based tree-state protocol in O(N) single-pass execution https://github.com/Recursive-Logic-Core/SLAP

- DriftBreak (v1.5.0): Local context governor & state-recovery engine mitigating context drift and VRAM payload overhead on 127.0.0.1 https://github.com/Recursive-Logic-Core/DriftBreak

- Deterministic Context Frameworks: Mitigating attention decay, sycophancy, and mid-context retrieval failure across massive multi-document spans https://github.com/Recursive-Logic-Core/llm-context-architec...

- Advanced Forensic Pattern Recognition: Signal extraction from extreme cryptographic and unstructured informational fragmentation (Rongorongo, Dorabella, Kryptos, Voynich) https://github.com/Recursive-Logic-Core/system-analysis

Terms: German employment contract & benefits (Open to international via EoR / German entity)

Languages: Native German, fluent written English (async-first)

Notice Period: 2 months to end of month

Email: [email protected]

Remote: Yes (100% Remote only)

Willing to relocate: No

Technologies: LLM Context Architecture, System Analysis, Python, Prompt/Logic Orchestration, Unstructured Data Forensics

Résumé/CV:

- Role: AI Systems Analyst (Concept & Orchestration)

- Focus: Designing structural logic frameworks and external control layers to solve core LLM limitations in enterprise environments (no traditional production coding).

- Deliverables: LLM Context Architectures for 500+ page docs (solving Lost-in-the-Middle), prevention of stochastic drift/hallucinations via audit layers, advanced pattern/anomaly detection (Rongorongo, Kryptos, Dorabella).

- Terms: German employment contract & benefits (Open to international via EoR / German entity)

- Languages: Native German, fluent written English (async-first)

- Notice Period: 2 months to end of month (German standard)

- LLM Context Architecture Repo: https://github.com/Recursive-Logic-Core/LLM-Context-Architec...

- System Analysis & Forensics Repo: https://github.com/Recursive-Logic-Core/system-analysis

Email: [email protected]