Senior AI Engineer

Role Summary

Senior AI Engineer to design, build, and evolve internal AI Agent ecosystem within the IT Engineering team. This role applies a high-level software engineering mindset to design complex, scalable agentic frameworks and platforms that systematically eliminate toil. You will define technical standards and build the resilient infrastructure that powers these agents, ensuring AI Agents drive operational velocity and support growth in the TechBio space. This is an office-based, hybrid role in Salt Lake City or New York City, with in-office requirement at least 50% of the time. The role has an estimated base annual salary range of $112,300 to $163,800, plus bonus, equity, and comprehensive benefits.

Responsibilities

• Architect and implement complex, multi-agent orchestration frameworks and AI Agents that autonomously handle business and scientific workflows, setting standards for how agents interact with sensitive data and legacy systems.
• Design and build core internal developer platforms and shared libraries to standardize agent deployment, enabling self-serve automations with built-in security and governance.
• Drive autonomous operations and infrastructure-as-code, engineering self-healing systems that manage configuration, identity, and system health with minimal human intervention.
• Establish observability standards (LLMOps) to debug non-deterministic AI behaviors, conduct root cause analyses, and engineer out failure modes.
• Partner with cross-functional leadership to translate high-level business goals into technical architectures, identifying opportunities where AI can restructure workflows.
• Serve as a technical leader for the AI Agent stack, elevating engineering standards through architectural decision records, code reviews, and mentorship.

Qualifications

• Required: 7+ years of software engineering experience with distributed systems and platform engineering; proven track record of architecting production-grade AI solutions in recent years.
• Mastery of Python and modern software design principles.
• Comprehensive command of the GenAI stack, including advanced RAG strategies, vector store architecture, and memory management for stateful agents.
• Demonstrated experience building shared libraries to enable scalable agent development.
• Expert-level understanding of API design and middleware strategies to securely integrate non-deterministic AI agents into complex enterprise ecosystems.
• Deep experience with LLMOps, including observability, evaluation frameworks, and debugging asynchronous agent workflows.
• Rigorous engineering approach to unknown unknowns, diagnosing bottlenecks and architecting permanent reliability and latency improvements.
• Superior communication skills to translate technical trade-offs into business value and influence stakeholders across departments.
• Proven track record of transformational impact and breaking down silos; collaborative mindset across functions.
• Willingness to iterate, experiment, and refine solutions; ownership mindset and accountability for outcomes; ethical integrity and trust; urgency in delivering impact.

Education

• Bachelor's degree in Computer Science or equivalent practical experience; advanced degrees or research experience in ML/AI are a plus.

Skills

• Python
• GenAI stack, including RAG, vector stores, memory management
• API design and middleware integration
• LLMOps, observability, evaluation frameworks
• Distributed systems and platform engineering
• Shared libraries and developer tooling
• Event-driven architectures and scalability