Senior AI Engineer

Recursion•Salt Lake, NY

32d•$112,300 - $163,800•Hybrid

About The Position

Your work will change lives. Including your own. The Role We are seeking a highly skilled Senior AI Engineer to design, build, and evolve our internal AI Agent ecosystem within the IT Engineering team. This role focuses on applying a high-level software engineering mindset to design complex, scalable agentic frameworks and platforms that systematically eliminate toil. You will be responsible for defining the technical standards and building the resilient infrastructure that powers these agents, ensuring our AI Agents drive operational velocity and effectively support our growth in the TechBio space. The Impact You'll Make Architect and implement complex, multi-agent orchestration frameworks and sophisticated AI Agents that autonomously handle business and scientific workflows, setting the standard for how agents interact with sensitive data and legacy systems. Design and build the core internal developer platforms and shared libraries that standardize agent deployment, allowing the wider organization to self-serve automations with built-in security and governance. Drive the strategy for autonomous operations and infrastructure-as-code, engineering self-healing systems that manage configuration, identity, and system health with minimal human intervention. Establish the observability standards (LLMOps) required to debug non-deterministic AI behaviors, conducting systemic root cause analyses to engineer out entire classes of failure modes and prevent recurrence. Partner with cross-functional leadership to translate high-level business goals into technical architectures, identifying high-leverage opportunities where AI can fundamentally restructure workflows rather than just patching them. Serve as a technical leader for our AI Agent stack, elevating the team’s engineering bar through architectural decision records, code reviews, and mentorship that fosters a culture of technical excellence. The Experience You'll Need 7+ years of software engineering experience, with a specific focus on distributed systems, platform engineering, and a proven track record of architecting production-grade AI solutions in recent years. Mastery of Python and deep familiarity with modern software design principles, creating code that is not just functional but a standard for others to follow. Comprehensive command of the GenAI stack, including advanced RAG strategies, vector store architecture, and memory management for stateful agents. Demonstrated experience building shared libraries; you won’t just build agents, you’ll build the tools that allow the organization to build agents at scale. Expert-level understanding of API design and middleware strategies to securely integrate non-deterministic AI agents into complex, deterministic enterprise ecosystems. Deep experience with LLMOps, specifically regarding observability, evaluation frameworks, and debugging complex, asynchronous agent workflows. A rigorous engineering approach to "unknown unknowns," with the ability to diagnose systemic bottlenecks and architect permanent solutions for reliability and latency. Superior communication skills with the ability to translate technical architectural trade-offs into business value, influencing stakeholders across non-technical departments. Demonstrated success in going beyond convention to drive transformational impact, rethinking what is possible rather than just optimizing what exists. A track record of breaking down silos and sharing knowledge freely, partnering deeply across functions to reveal new possibilities and ensure the team is greater than the sum of its parts. Proven ability to embrace iteration over perfection, actively experimenting, testing, and refining solutions because progress comes from doing. Experience taking ownership and accountability for decisive action, following through on commitments and owning outcomes rather than just tasks. Experience acting boldly with integrity, taking calculated risks and pushing boundaries without ever compromising on ethics, science, or trust. A history of operating with urgency because patients are waiting, prioritizing what matters most to move the needle every day.

Requirements

7+ years of software engineering experience, with a specific focus on distributed systems, platform engineering, and a proven track record of architecting production-grade AI solutions in recent years.
Mastery of Python and deep familiarity with modern software design principles, creating code that is not just functional but a standard for others to follow.
Comprehensive command of the GenAI stack, including advanced RAG strategies, vector store architecture, and memory management for stateful agents.
Demonstrated experience building shared libraries; you won’t just build agents, you’ll build the tools that allow the organization to build agents at scale.
Expert-level understanding of API design and middleware strategies to securely integrate non-deterministic AI agents into complex, deterministic enterprise ecosystems.
Deep experience with LLMOps, specifically regarding observability, evaluation frameworks, and debugging complex, asynchronous agent workflows.
A rigorous engineering approach to "unknown unknowns," with the ability to diagnose systemic bottlenecks and architect permanent solutions for reliability and latency.
Superior communication skills with the ability to translate technical architectural trade-offs into business value, influencing stakeholders across non-technical departments.
Demonstrated success in going beyond convention to drive transformational impact, rethinking what is possible rather than just optimizing what exists.
A track record of breaking down silos and sharing knowledge freely, partnering deeply across functions to reveal new possibilities and ensure the team is greater than the sum of its parts.
Proven ability to embrace iteration over perfection, actively experimenting, testing, and refining solutions because progress comes from doing.
Experience taking ownership and accountability for decisive action, following through on commitments and owning outcomes rather than just tasks.
Experience acting boldly with integrity, taking calculated risks and pushing boundaries without ever compromising on ethics, science, or trust.
A history of operating with urgency because patients are waiting, prioritizing what matters most to move the needle every day.

Nice To Haves

Bachelor's degree in Computer Science or equivalent practical experience; advanced degrees or research experience in ML/AI.
Experience with Knowledge Graphs and GraphRAG to structure connected data and reveal patterns that simple vector retrieval misses.
Hands-on experience fine-tuning open-weights models or utilizing Small Language Models (SLMs) for cost-efficient, low-latency, and secure internal tasks.
Familiarity with implementing guardrails and managing PII/PHI compliance to ensure we push boundaries without compromising ethics or trust.
Experience with Terraform or Pulumi to manage cloud resources at scale, treating infrastructure as a flexible, version-controlled software discipline.
Proficiency in designing event-driven architectures that allow agents to react instantaneously to complex business triggers.

Responsibilities

Architect and implement complex, multi-agent orchestration frameworks and sophisticated AI Agents that autonomously handle business and scientific workflows, setting the standard for how agents interact with sensitive data and legacy systems.
Design and build the core internal developer platforms and shared libraries that standardize agent deployment, allowing the wider organization to self-serve automations with built-in security and governance.
Drive the strategy for autonomous operations and infrastructure-as-code, engineering self-healing systems that manage configuration, identity, and system health with minimal human intervention.
Establish the observability standards (LLMOps) required to debug non-deterministic AI behaviors, conducting systemic root cause analyses to engineer out entire classes of failure modes and prevent recurrence.
Partner with cross-functional leadership to translate high-level business goals into technical architectures, identifying high-leverage opportunities where AI can fundamentally restructure workflows rather than just patching them.
Serve as a technical leader for our AI Agent stack, elevating the team’s engineering bar through architectural decision records, code reviews, and mentorship that fosters a culture of technical excellence.