AI Lead Software Architect - SME
Darkwolfsolutions · Chantilly/Herndon, VA
About this role
**Dark Wolf** constructs and deploys data management and analytics solutions for the defense and intelligence communities. We’re seeking an elite **AI Software Architect (SME)** to drive the vision, structural topology, and enterprise-wide architectural execution of mission-critical **AI/ML systems**—including fault-tolerant, resilient, ultra-low-latency distributed architectures deployed across **air-gapped, multi-cloud, and tactical edge** environments. --- ## Key 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 **RAG** platforms, and real-time semantic routing layers. - **Hardware & Inference Optimization:** Lead system trade studies to optimize compute across heterogeneous hardware (GPUs, TPUs, NPUs), including quantization, speculative decoding, and custom execution kernels. - **Zero-Trust Security & Governance:** Establish system-wide AI security postures (automated DevSecOps, prompt-injection guardrails, differential privacy, and supply-chain risk management for ML artifacts). - **Technical Authority & Roadmap Strategy:** Partner with executive leadership and intelligence community stakeholders to map mission objectives to technical architectures, establish coding/safety standards, and direct R&D initiatives. --- ## Required Qualifications - Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field *(Master’s or Ph.D. strongly preferred).* - **15+ years** of software engineering and systems architecture experience with leadership delivering enterprise-scale AI/ML solutions. - **AI Frameworks & LLMOps:** PyTorch, TensorRT-LLM, vLLM, DeepSpeed, Ray; custom extension development; enterprise orchestration platforms (LangGraph, AutoGen, LlamaIndex). - **AI Models & Fine-Tuning Strategy:** speculative decoding, MoE, 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, deterministic evaluation. - **Systems Programming & Performance:** Java, Rust, Python, C; asynchronous execution, memory management, CUDA/Triton kernels, hardware-level performance profiling. - **Containerization & Mesh Orchestration:** Kubernetes multi-cluster federation, custom CRDs, Istio service mesh, bare-metal GPU scheduling, zero-trust containerization. - **Multi-Cloud & Air-Gapped Infrastructure:** AWS GovCloud, Azure Secret; IaC (Terraform, Pulumi); disconnected/air-gapped tactical node deployment. - **DevSecOps & AI Security Tooling:** automated SAST/DAST, TEEs, runtime guardrails, adversarial AI defense, automated vulnerability remediation. - **Agile & Enterprise Transformation:** lead multi-pod engineering teams, SAFe/Scaled Agile execution, manage architectural debt across multi-year programs. --- ## Desired Qualifications - **Advanced Certifications:** AWS Certified Solutions Architect – Professional, CISSP, CKA, and/or specialized HPC credentials. - **Pioneering Field Work:** experience architecting/deploying petabyte-scale ML systems or multi-agent autonomous frameworks into classified, air-gapped networks. - **Recognized Technical Leadership:** open-source contributions, technical publication
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