Staff AI Engineer – Applied AI & Autonomous Agents

Ruxlo; New Jersey; On-site; USD 180,000 - 320,000; Full time

Job summary

Ruxlo is hiring a Staff Software Engineer, Applied AI in the United States. You will set the technical strategy for integrating AI into the product, from a single LLM call to long-running autonomous agents, and serve as the technical anchor for applied AI across teams.

You will own end-to-end AI architecture, ship LLM-powered features like natural language search and extraction, build durable agent workflows, and ensure safe, auditable usage with cost-aware design and robust evaluation.

Qualifications

• 8+ years of engineering experience with a technical lead role.
• LLM-powered features shipped to real users (retrieval-augmented search, extraction or classification).
• At least one autonomous, non-conversational agent brought to production with user-initiated actions.

Responsibilities

• Own the architecture of AI systems end-to-end: model access, retrieval, prompts, tools, agents, and cost.
• Ship LLM-powered features like natural language search, summarization, extraction and classification on records.
• Develop durable, long-running agent workflows with safe resume after failure.
• Build agents that act on a user’s behalf with consent and audit trails.
• Establish evaluation, CI gates, and cost-merting for AI features.

Skills

Strong ownership

Excellent communication

Independent work

Ambiguity tolerance

Decision making

AI tooling

Cross-functional collaboration

Open to feedback

Tools

Python

TypeScript

PostgreSQL

Docker

Kubernetes

AWS

Job description

Ruxlo is hiring a Staff Software Engineer, Applied AI in the United States. You will set the technical strategy for integrating AI into the product, from a single LLM call to long-running autonomous agents, and serve as the technical anchor for applied AI across teams.

You will own end-to-end AI architecture, ship LLM-powered features like natural language search and extraction, build durable agent workflows, and ensure safe, auditable usage with cost-aware design and robust evaluation.