AI Lead Software Architect - SME

Posted Yesterday
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2 Locations
In-Office
225K-285K Annually
Expert/Leader
Information Technology
The Role
Lead enterprise AI software architecture for distributed, mission-critical systems in classified, air-gapped, multi-cloud, and tactical edge environments. Design LLM platforms, multi-agent systems, RAG solutions, inference pipelines, hardware-optimized execution, zero-trust security, and DevSecOps architectures. Serve as the principal technical authority, establish engineering standards, guide roadmaps, lead research initiatives, and collaborate with executive and intelligence-community stakeholders.
Summary Generated by Built In

Dark Wolf constructs and deploys data management and analytics solutions for the defense and intelligence communities. We’re proud to boast a world-class engineering team that thrives on rolling up their sleeves to solve your mission’s biggest challenges.
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.

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 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.

Required Qualifications:

  • 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.

Desired Qualifications:

  • 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).


Position Clearance Requirement: 

US Citizenship with an active TS/SCI security clearance with Full-Scope Polygraph


Location:
  Chantilly/Herndon, VA. 

Target Salary Range: $225,000.00 – $285,000.00+ (Commensurate with specialized architecture expertise and technical skillset)

Equal Opportunity Employer:

We are proud to be an EEO/AA employer Minorities/Women/Veterans/Disabled and other protected categories. In compliance with federal law, all persons hired will be required to verify identity, confirm US Citizenship, and complete the required employment eligibility verification upon hire.

We are strictly looking for direct, full-time W2 employees. We do not engage with third-party staffing agencies, C2C, or 1099 independent contractors for this role.

Skills Required

  • Bachelor's degree in Computer Science, Information Systems, Engineering, or a related technical field
  • 15+ years of software engineering and systems architecture experience
  • Leadership experience delivering enterprise-scale AI and machine learning solutions
  • Advanced mastery of PyTorch, TensorRT-LLM, vLLM, DeepSpeed, Ray, LangGraph, AutoGen, and LlamaIndex
  • Expertise in AI architecture adaptation, speculative decoding, mixture-of-experts, LoRA, QLoRA, RLHF, DPO, and GRPO
  • Experience architecting MLOps and LLMOps, model governance, continuous training, drift detection, and deterministic evaluation systems
  • Mastery of Java, Rust, Python, and C, including asynchronous execution, memory management, CUDA/Triton kernels, and hardware performance profiling
  • Experience with enterprise Kubernetes multi-cluster federation, custom CRDs, Istio service mesh, bare-metal GPU scheduling, and zero-trust containerization
  • Experience with AWS GovCloud, Azure Secret, Terraform, Pulumi, and disconnected or air-gapped tactical deployments
  • Experience designing SAST/DAST pipelines, confidential computing enclaves, runtime guardrails, adversarial AI defenses, and vulnerability remediation frameworks
  • Experience leading multi-pod engineering teams, implementing SAFe or scaled agile execution, and managing architectural debt
  • US citizenship
  • Active TS/SCI security clearance with Full-Scope Polygraph
  • Master's degree or Ph.D. in a related technical field
  • AWS Certified Solutions Architect Professional certification
  • Certified Information Systems Security Professional certification
  • Certified Kubernetes Administrator certification
  • Specialized High-Performance Computing credentials
  • Experience deploying petabyte-scale ML systems or multi-agent autonomous frameworks into classified, air-gapped intelligence networks
  • Open-source contributions, technical publications, or patents in distributed AI systems or architectures
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The Company
HQ: Chantilly, VA
99 Employees
Year Founded: 2009

What We Do

Dark Wolf Solutions provides DevSecOps agile software development, information operations, penetration testing and incident response, applied research and rapid prototyping, machine learning, and mission support and engineering services to the Intelligence Community, national security, and Fortune 500 customers. By combining the most innovative emerging technologies with deep federal domain expertise, Dark Wolf operates at the nexus of technical innovation and mission needs.

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