Senior AI Systems Architect: Ultra-Low-Latency, Air-Gapped

BuddoBot Inc.

Chantilly (VA)

On-site

USD 225,000 - 285,000

Full time

14 days+

Application generator

An application made for this job — a tailored resume and cover letter that speak straight to the posting.

Get past ATS filters

Job summary

Dark Wolf in Chantilly/Herndon, VA seeks an elite AI Software Architect (SME) to drive the vision, topology, and enterprise-wide architectural execution of mission-critical AI/ML systems across air-gapped, multi-cloud, and tactical edge environments.

You will serve as the principal technical authority, bridging high-assurance systems engineering with cutting-edge AI models, custom inference engines, multi-agent frameworks, and zero-trust DevSecOps pipelines.

Qualifications

Bachelor's degree in Computer Science, Information Systems, Engineering, or a related technical field (Master's degree or Ph.D. strongly preferred).
15+ years of software engineering and systems architecture experience, with demonstrated leadership in delivering enterprise-scale AI/ML solutions.
AI Frameworks & LLMOps: Advanced mastery of low-level framework mechanics (PyTorch, TensorRT-LLM, vLLM, DeepSpeed, Ray), custom extension development, and enterprise orchestration platforms (LangGraph, AutoGen, LlamaIndex).
AI Models & Fine-Tuning Strategy: Expertise in novel architecture adaptation, speculative decoding, mixture-of-experts (MoE), parameter-efficient fine-tuning (LoRA, QLoRA), and post-training alignment (RLHF, DPO, GRPO).
Machine Learning Systems Engineering: MLOps/LLMOps architecture, model governance, continuous training pipelines, real-time drift detection, and deterministic evaluation frameworks.
Systems Programming & Performance: Polyglot mastery in Java, Rust, Python, and C, with deep expertise in asynchronous execution, memory management, CUDA/Triton kernels, and hardware-level performance profiling.
Containerization & Mesh Orchestration: Enterprise Kubernetes multi-cluster federation, custom CRDs, Service Mesh (Istio), bare-metal GPU scheduling, and zero-trust containerization strategies.
Multi-Cloud & Air-Gapped Infrastructure: Cross-cloud architecture (AWS GovCloud, Azure Secret), Infrastructure as Code (Terraform, Pulumi), and disconnected/air-gapped tactical node deployment methodologies.
DevSecOps & AI Security Tooling: Designing automated SAST/DAST pipelines, confidential computing enclaves (TEEs), runtime guardrails, adversarial AI defense, and automated vulnerability remediation frameworks.
Agile & Enterprise Transformation: Steering multi-pod engineering teams, establishing SAFe/Scaled Agile systems execution, and managing architectural debt across multi-year programs.

Responsibilities

Enterprise AI System Design: Architect end-to-end distributed AI platforms, high-throughput model inference pipelines, and scalable enterprise LLM/SLM deployment topologies tailored for classified enclaves.
Autonomous & Agentic Systems: Design resilient multi-agent orchestration engines, continuous Retrieval-Augmented Generation (RAG) platforms, and real-time semantic routing layers using modern framework paradigms.
Hardware & Inference Optimization: Lead system trade studies to optimize compute across heterogeneous hardware (GPUs, TPUs, NPUs), implementing advanced quantization, speculative decoding, and custom execution kernels for edge and air-gapped environments.
Zero-Trust Security & Governance: Establish system-wide AI security postures, incorporating automated DevSecOps, prompt-injection guardrails, differential privacy, and rigorous supply-chain risk management for ML artifacts.
Technical Authority & Roadmap Strategy: Interface directly with executive leadership and intelligence community stakeholders to map mission objectives to technical architectures, establish enterprise coding and safety standards, and direct R&D initiatives.