> Markdown version of [/jobs/ext/4012479-ai-lead-software-architect-sme](https://www.wearedevelopers.com/jobs/ext/4012479-ai-lead-software-architect-sme). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Lead Software Architect - SME - **Company:** Dark Wolf Solutions - **Location:** Herndon, VA, United States - **Experience:** Expert - **Salary:** $225,000.0 - $285,000.0 - **Contract:** Permanent contract - **Skills:** LangGraph Framework, C (Programming Language), Java (Programming Language), Agile Methodology, Artificial Intelligence, Amazon Web Services, Data Analysis, Systems Engineering, Microsoft Azure, Cloud Engineering, Nvidia CUDA, Information Systems, Memory Management, Fault Tolerance, Information Systems Security Architecture Professional, Python (Programming Language), Machine Learning, Performance Tuning, Software Architecture, Inference Optimization, Zero Trust Network Access, Software Engineering, Systems Architecture, System Programming, Software Vulnerability Management, Rust (Programming Language), Pulumi, QLoRA, Graphics Processing Unit (GPU), High Performance Computing, Pytorch, DeepSpeed, Istio, Large Language Models, Multi-Agent Systems, Multi-Cloud, Llamaindex, Differential Privacy, Generative AI, Agentic-AI, Containerization, AI Platforms, Kubernetes, Information Technology, Low Latency, Bare Metal, AutoGen, Free and Open-Source Software, Hardware Acceleration, Data Management, Machine Learning Operations, TensorRT, Drift Detection, VLLM, Decoding, Terraform, Devsecops, Static Application Security Testing, Dynamic Application Security Testing - **Published:** October 29, 2026 - **Apply:** https://www.careerbuilder.com/job-details/ai-lead-software-architect-sme-va--8a923234-4ffa-41c9-9463-1ab1dd1f7721 ## About the Role Software Architecture, Artificial Intelligence (AI), Data Management, Defense Intelligence, Data Analysis, Artificial Intelligence (AI), Software Engineering, Topology, Machine Learning, Software Architecture, * A 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., * Advanced Certifications: AWS Certified Solutions Architect - Professional, Certified Information Systems Security Professional (CISSP), Certified Kubernetes Administrator (CKA), or specialized High-Performance Computing (HPC) credentials. * Pioneering Field Work: Proven track record architecting and deploying petabyte-scale ML systems or multi-agent autonomous frameworks into classified, air-gapped intelligence networks. * Recognized technical leadership in the broader AI engineering community (e.g., open-source contributions, technical publications, or patent holdings in distributed AI systems/architectures). ## Description Dark Wolf is seeking an elite AI Software Architect (SME) to drive the vision, structural topology, and enterprise-wide architectural execution of mission-critical Artificial Intelligence and Machine Learning systems. Operating at the apex of software engineering and hardware acceleration, you will design fault-tolerant, resilient, and ultra-low-latency distributed AI architectures deployed across air-gapped, multi-cloud, and tactical edge environments. In this role, you will serve as the principal technical authority, bridging high-assurance systems engineering with bleeding-edge AI models, custom inference engines, multi-agent frameworks, and zero-trust DevSecOps pipelines., * 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.