Principal Software Engineer (AI)

TL;DR

Principal Software Engineer (AI): Leading a multi-functional team to architect and deliver intelligent AI agents for HR and Finance workflows with an accent on LLM orchestration, RAG, and enterprise-grade system integration. Focus on defining tooling strategy, scaling AI agent pipelines, and ensuring reliability and compliance within a complex cloud environment.

Location: Must be based in the USA. This is a hybrid role requiring at least 50% of time spent in the office or in the field per quarter.

Salary: $197,000 – $334,300 USD (based on location and experience).

Company

A Fortune 500 company and leading AI platform for managing people, money, and agents, dedicated to shaping the future of work.

What you will do

• Lead a high-performing team of engineers to deliver AI-powered agents integrated into HR and financial workflows.
• Evaluate, select, and integrate AI tools, frameworks, and platforms to ensure scalability and compliance.
• Collaborate with product, engineering, and data science teams to implement AI-based automation solutions.
• Establish monitoring, feedback loops, and continuous learning mechanisms to improve agent performance.
• Architect intelligent agents using LLMs, RAG, and orchestration frameworks like LangGraph.
• Build responsible AI into the Agent Factory pipeline supporting various enterprise systems.

Requirements

• Must be based in the USA.
• 8+ years of experience in product engineering leading the delivery of highly available cloud products.
• 5+ years of experience in AI, machine learning, or intelligent automation for enterprise applications.
• 2+ years of experience with LLMs, AI agents, and orchestration frameworks such as LangGraph.
• 5+ years of experience with Python, cloud AI services (AWS, Azure, GCP), and model deployment.
• Proven track record of translating complex business challenges into innovative, AI-powered solutions.

Nice to have

• Hands-on experience with vector databases and fine-tuning LLMs.
• Experience with data privacy, security, and compliance for AI in enterprise environments.
• Experience with large-scale dataset management, including collection, labeling, and validation.

Culture & Benefits

• Flexible work approach emphasizing intentional in-person collaboration.
• Comprehensive benefits package including health, stock grants, and bonus plans.
• Culture rooted in integrity, empathy, and shared enthusiasm.
• Investment in long-term professional development and skill growth.