Principal AI Engineer – Automation & AI

Role Overview

• Design and deploy agentic AI workflows and automation solutions across enterprise functions including R&D, Engineering, Professional Services, IT, Finance, Sales, and Marketing
• Build production-grade systems such as:
• Multi-agent workflows
• RAG-based applications
• Document intelligence and summarization pipelines
• Workflow and process automation solutions
• Use modern AI tools and frameworks including:
• Codex, Claude Code, Gemini, NotebookLM
• LangChain, LangGraph, LlamaIndex (or equivalents)
• Rapidly prototype, validate, and deploy solutions in weeks, not months
• Translate business problems into working AI systems
• Design lightweight architectures and iterate quickly
• Develop and implement:
• Prompt engineering strategies
• Orchestration logic
• API integrations and data pipelines
• Testing, validation, and monitoring frameworks
• Partner directly with stakeholders to refine outputs and drive adoption
• Deliver continuous output with weekly or bi-weekly releases
• Prioritize use cases based on:
• ROI and business impact
• Technical feasibility
• Speed to value
• Operate with minimal process and high accountability in a fast-paced environment
• Build and maintain reusable assets including:
• Prompt templates
• Agent design patterns
• Integration utilities
• Contribute to lightweight standards for:
• Security and data handling
• Responsible AI practices
• Evaluation and performance monitoring
• Provide technical guidance to a small team of AI engineers and automation specialists
• Lead by example through hands-on contribution
• Support the evolution of the AI engineering function as it scales

Requirements

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field
• 6–10+ years of software engineering experience with recent hands-on work in AI/LLM systems
• Proven experience building and deploying:
• LLM-powered applications
• Agentic workflows
• Automation solutions in production environments
• Strong hands-on experience with tools such as:
• Codex, Claude Code, Gemini, NotebookLM (or similar AI-assisted development tools)
• LangChain, LangGraph, LlamaIndex, or equivalent frameworks
• Proficiency in:
• Python
• API development and system integration
• Cloud platforms (AWS, Azure, or GCP)

Tech Stack

• AWS
• Azure
• Cloud
• Google Cloud Platform
• Python

Benefits

• Health insurance
• Retirement plans
• Paid time off
• Flexible work arrangements
• Professional development