Senior AI Engineer, Agentic Systems

Role Overview

This is a high-impact engineering role focused on designing and delivering production-grade agentic AI systems that orchestrate tools, data, and policies to solve real enterprise workflows.

What You Will Do

Design and implement multi-agent architectures, build and optimize RAG pipelines, integrate enterprise systems and data sources, and develop evaluation frameworks to measure accuracy, safety, cost, and task success.

Why It Might Be a Fit

Ideal for an engineer who thrives in greenfield architecture and enjoys turning cutting-edge AI capabilities into practical, scalable systems.

Requirements

• 5–8+ years of experience in software engineering or platform engineering
• Strong experience with agentic frameworks such as LangGraph, LangChain Agents, AutoGen, CrewAI, or equivalent systems
• Deep understanding of RAG architectures including embedding strategies, vector databases, chunking, ranking, and grounding techniques
• Proven ability to build observable, secure, and cost-efficient AI systems with strong engineering discipline around testing and CI/CD
• Strong software engineering fundamentals in Python or TypeScript, including async programming, APIs, and distributed system design
• Experience implementing evaluation, monitoring, and observability systems for AI workflows
• Familiarity with enterprise security, privacy, and compliance requirements
• Strong communication skills with the ability to work directly with clients and translate requirements into technical designs
• Experience with Azure or other cloud platforms and containerized deployment environments

Benefits

• Competitive and flexible compensation package
• Remote-first flexibility
• Opportunity to work on cutting-edge production agentic AI systems
• High autonomy in system design and architecture decisions
• Strong culture of learning and experimentation
• Exposure to modern AI tooling and frameworks
• Inclusive and flexible work environment
• Opportunity to shape foundational AI systems used in real business-critical workflows