AI Lead Software Architect - SME

United StatesUnited States·Chantilly/herndonlead
EngineeringSoftware Architect
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Quick Summary

Key Responsibilities

Architect end-to-end distributed AI platforms, high-throughput model inference pipelines, and scalable enterprise LLM/SLM deployment topologies tailored for classified enclaves.

Requirements Summary

A Bachelor's degree in Computer Science, Information Systems, Engineering, or a related technical field (Master’s degree or Ph.D. strongly preferred).

Technical Tools
EngineeringSoftware Architect

Responsibilities

~1 min read
  • 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.

Requirements

~2 min read
  • 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).

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

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.

Location & Eligibility

Where is the job
Chantilly/herndon, United States
On-site at the office
Who can apply
US

Listing Details

Posted
May 27, 2026
First seen
May 27, 2026
Last seen
September 20, 2026

Posting Health

Days active
36
Repost count
0
Trust Level
23%
Scored at
July 3, 2026

Signal breakdown

freshnesssource trustcontent trustemployer trust
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AI Lead Software Architect - SME