Senior AI Software Engineer (LLM & Agent Systems)

Company Overview

Our client is a fast-growing technology company building modern, data-driven products with a strong focus on leveraging AI to create scalable systems and internal efficiencies. Their team is focused on moving fast, shipping high-quality solutions, and using the latest advancements in AI to multiply engineering output across the organization.

They are particularly focused on applying AI not as a feature, but as a core layer of how work gets done—automating workflows, enhancing product capabilities, and enabling small teams to achieve outsized impact.

Role Overview

We are looking for a full-time (40 hours/week) Senior AI Systems Engineer who operates natively with AI tools and builds production-ready systems using agents and LLM workflows.

This role requires someone who has gone beyond basic AI usage and can design and deploy systems that automate work, integrate tools, and significantly increase engineering productivity.

You will work in the EST time zone, collaborating closely with cross-functional teams to identify opportunities where AI can replace manual processes and unlock efficiency.

Key Responsibilities

• Build and deploy AI agents for internal and user-facing workflows
• Design systems that retrieve, process, and act on data autonomously
• Integrate APIs, tools, and data sources into AI-driven workflows
• Use tools like Claude/Codex to accelerate development and output
• Identify and implement AI-driven automation opportunities across teams
• Continuously experiment with new AI capabilities and approaches

Requirements

• Proven experience building AI agents or LLM-powered systems
• Deep, hands-on usage of Claude, Codex, or similar tools
• Strong backend or full-stack engineering experience (Python, JavaScript, Ruby, Go, Elixir, etc.)
• Ability to independently ship complex systems
• Experience integrating APIs and building scalable workflows

Preferred Qualifications

• Experience with vector databases (Pinecone, PgVector, etc.)
• Exposure to data pipelines or data infrastructure
• Experience building internal automation tools

Key Traits

• Builder mindset and high ownership
• Strong focus on productivity and leverage
• Demonstrated portfolio of AI-driven projects