# AI Lead Software Architect - SME

**Company**: Dark Wolf
**Location**: Chantilly, VA
**Work arrangement**: onsite
**Experience**: senior
**Job type**: full-time
**Salary**: $225,000.00 – $285,000.00+
**Category**: Engineering
**Industry**: Technology

**Apply**: https://job-boards.greenhouse.io/darkwolfsolutions/jobs/7748609003?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_a0331986-c3c

## 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.

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.

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

## Skills

### Required
- AI Frameworks & LLMOps
- AI Models & Fine-Tuning Strategy
- Machine Learning Systems Engineering
- Systems Programming & Performance
- Containerization & Mesh Orchestration
- Multi-Cloud & Air-Gapped Infrastructure
- DevSecOps & AI Security Tooling
- Agile & Enterprise Transformation
- Python
- Java
- Rust
- C
- Kubernetes
- Terraform
- Pulumi
- AWS GovCloud
- Azure Secret

### Nice to have
- Advanced Certifications
- Pioneering Field Work
- Recognized technical leadership

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Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/darkwolfsolutions/jobs/7748609003?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)