Sr. AI Systems Engineer

The Sr. AI Systems Engineer is a technically sophisticated individual contributor responsible for designing, developing, and deploying agentic AI tools and autonomous workflows that eliminate manual bottlenecks and unlock operational leverage across the organization. This role sits at the intersection of software engineering and AI/LLM architecture—translating complex business processes into intelligent, self-executing systems. The AI Systems Engineer brings deep engineering instincts to a fast-evolving toolset, building solutions that are not only functional but observable, maintainable, and aligned to strategic priorities. 

Design and develop agentic AI workflows using LLM orchestration frameworks while implementing planning, reflection, and tool-use patterns

Architect and build system integrations connecting AI agents to internal APIs, databases, and third-party SaaS platforms

Develop and maintain Human-in-the-Loop (HITL) checkpoints and escalation logic to surface agentic decisions for human validation

Implement observability and feedback loops within deployed agents to capture performance signals, exception rates, and decision traces

Analyze existing technical workflows to identify automation opportunities and produce engineering-ready specifications

Contribute to documentation standards for agentic systems including technical specs, architecture diagrams, and runbooks

Partner with internal stakeholders to translate operational pain points into technical requirements

Conduct all business in accordance with company policies and procedures

Perform all other duties as assigned

Education and Experience

• Typically requires a minimum of 3 years of related experience with a Bachelor's degree or 2 years with a Master's degree

• Preferred 3+ years in software or systems engineering with at least 1 year focused on LLM-based automation or agentic system design

• Bachelor's degree in Computer Science, Software Engineering, or a related technical field preferred

Knowledge and Abilities

• Proficiency in Python and at least one LLM orchestration framework such as LangChain, LlamaIndex, or CrewAI

• Strong API integration skills across REST and GraphQL including comfort with various authentication patterns

• Working knowledge of prompt engineering, retrieval-augmented generation (RAG), and tool/function calling patterns

• Experience with SQL and NoSQL databases including schema design for agentic memory and state management

• Familiarity with cloud environments and deployment patterns for AI workloads

• Version control proficiency using Git with disciplined branching and documentation practices

• Ability to decompose complex processes into discrete and testable automation components

• Experience designing observability into systems including logging, alerting, and performance tracking

• Ability to communicate technical architecture and tradeoffs clearly to non-technical stakeholders

• Comfort working across functions to gather requirements and iterate on agent behavior