Location: Remote

Salary: $120,000 - $180,000 + Benefits

We are seeking an AI Engineer to design and deploy AI-powered solutions that automate real business processes and improve operational efficiency. This role focuses on building intelligent agents, developing user-facing applications, and ensuring AI systems are reliable, scalable, and trusted by end users. You'll work closely with stakeholders to identify automation opportunities and deliver impactful AI solutions in a fast-growing, AI-driven environment.

Responsibilities

• Identify and evaluate business workflows suitable for AI-driven automation.
• Design, build, and deploy AI agents that automate operational tasks end-to-end.
• Develop user-facing applications and interfaces that make AI outputs accessible and trustworthy.
• Define success criteria and build testing frameworks to evaluate AI performance.
• Monitor and improve AI systems based on accuracy, reliability, cost, and response times.
• Partner with data teams to ensure agents are grounded in trusted, high-quality data.
• Establish and maintain appropriate data access, security, and governance controls.
• Document system functionality, capabilities, and performance metrics.

Qualifications

• 1-2 years experience building and deploying AI/LLM-powered applications in production environments.
• Strong software engineering fundamentals, including testing, version control, and code reviews.
• Experience developing customer-facing or internal business applications.
• Proficiency with SQL and working with large-scale data environments.
• Understanding of AI agent architectures, retrieval systems, grounding techniques, and evaluation methodologies.
• Experience measuring and improving AI system performance and reliability.
• Strong communication skills with the ability to collaborate across technical and business teams.
• Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field (or equivalent experience).

Preferred Qualifications

• Experience with AI agent frameworks, model APIs, and tool-calling architectures.
• Familiarity with AI evaluation, monitoring, and observability platforms.
• Knowledge of semantic search, vector databases, and retrieval-augmented generation (RAG).
• Experience optimizing inference costs and application performance.
• Understanding of AI governance, data privacy, and access controls.