AI Engineer (Agentic AI & LLMs)

Rise Technical; United States; On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Medical Insurance

PTO

Job summary

Rise Technical Recruitment Ltd is seeking an AI Engineer to own autonomous, multi-agent LLM systems in a fast-growing cybersecurity AI startup. You will design, implement and optimize production-grade agents, integrating tool use and planning loops within Kubernetes to scale deployments and reduce latency.

You will work with data curation, fine-tuning, and evaluation, collaborating with engineering leadership and cross-functional teams to move experiments into robust, scalable enterprise

Qualifications

• Production ML systems experience, especially with LLM-powered agents.
• Strong Python programming with PyTorch and Hugging Face.
• Experience 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 (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

Skills

LLM architectures

Python

PyTorch

Hugging Face

Tools

TensorRT-LLM

vLLM

Job description

$180,000 -$240,000 + Medical Insurance + PTO

Are you an 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