Senior AI Engineer (LLMs / Agents)

Rise Technical; United States; Hybrid; USD 180,000 - 250,000; Full time

Benefits offered by this job

Equity

Healthcare

PTO

Job summary

Rise Technical is seeking a Senior AI Engineer in the United States to take ownership of multi-agent architectures within a high-growth cybersecurity AI start-up. This position involves designing sophisticated systems and fine-tuning models while working with a specialized AI team to solve complex security challenges.

The ideal candidate will have a strong background in Python, production ML systems, and experience with LLMs. Competitive compensation includes equity, healthcare, and PTO.

Qualifications

• Experience building production ML systems, focusing on LLMs or LLM-powered agents.
• Shipping multi-agent or tool-using LLM systems to production.

Responsibilities

• Design and improve multi-agent architectures, planning loops, and tool-use.
• Contribute to model training via data curation, Supervised Fine-Tuning, and preference optimization.
• Build evaluation harnesses to track model and agent performance.
• Optimize inference for latency and throughput using vLLM or TensorRT-LLM.
• Deploy and scale production agents within Kubernetes environments.

Skills

Production ML systems

Strong Python programming

PyTorch

Hugging Face

Supervised Fine-Tuning

Preference optimization

Synthetic data generation

Tools

Kubernetes

vLLM

TensorRT-LLM

Job description

$180,000 - $250,000 + Equity + Healthcare + PTO

Are you a Senior AI Engineer with experience building production‑grade LLM systems looking to take ownership of autonomous, multi‑agent architectures within a high‑growth cybersecurity AI start‑up?

This is an opportunity to join a fast‑growing AI company developing next‑generation autonomous offensive security platforms. You will join a specialized AI engineering team and play a critical role in advancing their flagship platform, moving the needle on complex problems like exploit chaining, multimodal vision, and co‑evolutionary self‑training loops.

In this role, you will design, implement, and optimize highly sophisticated multi‑agent architecture, while contributing directly to model fine‑tuning and production scalability. Working closely with engineering leadership and cross‑functional teams, you will transition advanced multi‑agent systems from cutting‑edge experimentation into robust, production‑ready enterprise solutions.

This role would suit an AI Engineer who enjoys solving deep, technical agent‑orchestration challenges and wants to be a foundational builder of autonomous, self‑improving security systems.

The Role:

• Design and improve multi‑agent architectures, planning loops, and tool‑use
• Contribute to model training via data curation, Supervised Fine‑Tuning, and preference optimization (DPO/GRPO)
• Build evaluation harnesses to track model and agent performance
• Optimize inference for latency and throughput using vLLM or TensorRT‑LLM
• Deploy and scale production agents within Kubernetes environments

The Person:

• Experience building production ML systems, with a strong focus on LLMs or LLM‑powered agents
• Strong Python programming alongside PyTorch and Hugging Face
• Experience with Supervised Fine‑Tuning, preference optimization, and synthetic data generation
• Experience shipping multi‑agent or tool‑using LLM systems to production