Applied AI Architect

Hybrid Details

Onsite 3 days/week (Tuesday-Thursday)

​Austin, Texas client is seeking an Applied AI Architect with deep experience bridging LLM/SLM model research and enterprise productization. You will lead the technical direction from model architecture selection, fine‑tuning, and optimization to deployment and observability, shaping the next generation of agentic AI for cybersecurity. This role demands both foundational knowledge and production practicality designing and validating novel approaches, then translating them into reliable, scalable solutions deployed in the client's platform.

• Drive research-to-production of LLM/SLM systems from design and fine‑tuning to evaluation, deployment, and continual adaptation in enterprise agent workflows.
• Lead technical choices determining when to apply context engineering, prompt tuning, continued pretraining, supervised fine‑tuning, reasoning fine‑tuning, LoRA, or RL.
• Architect high‑performance inference and serving using vLLM, NVIDIA NIM, Triton, CUDA, or other optimized frameworks.
• Integrate reinforcement learning frameworks (veRL, SkyRL, PyTorch, Ray RLlib) to enhance reasoning, adaptability, and agent feedback loops.
• Develop and operationalize AI Ops pipelines, build benchmarks and metrics for model evaluation, observability, drift detection, and lifecycle automation.
• Advance agent interoperability using A2A (Agent‑to‑Agent) or MCP (Model Context Protocol) for large‑scale coordination.
• Collaborate with cybersecurity researchers to embed threat reasoning, anomaly detection, and defensive logic directly into model behavior.
• Publish, document, and codify reusable AI blueprints for hybrid (cloud + on‑prem) deployments and future research acceleration.

• Proven end‑to‑end experience bringing LLM/SLM research into production from fine‑tuning and inference optimization to evaluation and AI Ops integration. Excellent knowledge of at least one of the following:
• Deep understanding of data‑model‑infrastructure trade‑offs and optimization under real business constraints.
• Hands‑on experience fine‑tuning LLMs using frameworks such as LLaMA Factory, NeMo, and PEFT (e.g., LoRA)
• Strong knowledge of GPU‑accelerated inference (ex: vLLM, NIM, Triton, CUDA, NCCL, PyTorch/XLA).
• Familiarity with AI Ops tool chains (ex: Weights & Biases, MLflow, Ray Serve).
• Proficiency in Python, and experience building containerized AI microservices (ex: Docker, Kubernetes, Ray).
• 8+ years of software engineering or research engineering experience, including the most recent 3 years focused on applied AI/ML and deploying LLM/SLM systems in production at enterprise scale.
• Proven experience as a Senior technical lead or architect, driving end to end design, roadmap decisions, and productization of AI systems.
• Deep expertise in cloud‑native architecture across AWS, Azure, or GCP.
• Experience in mentoring senior engineers, reviewing technical designs, and establishing engineering best practices.

• Demonstrated success in building scalable infrastructure and launching LLM/SLM‑based features and agent systems within enterprise platforms.
• Expertise in quantization, distillation, or GPU profiling to lower inference cost.
• Clear conceptual understanding of when to fine‑tune vs prompt‑engineer vs use RLHF and evidence of having applied each effectively.
• Familiarity with agentic frameworks (Lang Chain, AWS Strands, Auto Gen, etc).
• Deep understanding of A2A/MCP protocols for interoperable multi‑agent systems.

• Research‑driven yet delivery‑focused capable of balancing innovation with practical deployment.
• Data‑ and results‑oriented every hypothesis must be measurable.
• Ownership mentality from exploration and experiment to evaluation, optimization, and monitoring.
• Passionate about turning AI research into defensible, intelligent, and proactive cybersecurity systems.

This position does not offer sponsorship for work permit applications or renewals, either now or in the future. Candidates must be authorized to work in the U.S. without the need for employment‑based visa sponsorship, both currently and moving forward.