Manager of Artificial Intelligence

Role:
Senior Member of Technical Staff, Applied AI

Space:
Agentic AI x Life Sciences

Location:
New York City (Onsite)

Interested in owning the technical direction of production AI systems rather than simply building against an existing roadmap?

We're partnered with a fast-growing, venture-backed AI company building complex enterprise software within life sciences.

They're looking for a senior Applied AI engineer to take ownership across the architecture and evolution of their AI systems, working across retrieval, generation, verification, evaluation, and production reliability.

This is a high-impact IC role for someone who wants to make the difficult technical decisions, define how AI quality is measured, and have significant influence over both the product and wider technical direction.

• Own the technical direction of production LLM and agentic systems
• Architect systems across retrieval, generation, verification, and evaluation
• Develop sophisticated evaluation frameworks for AI problems where ground truth is complex or slow to obtain
• Build systems that maintain strong grounding and provenance across complex proprietary datasets
• Connect AI outputs with real-world performance data to continuously improve system quality
• Identify and measure behavioural regressions as models, prompts, retrieval systems, and architectures evolve
• Evaluate different approaches across RAG, agents, prompting, and targeted fine-tuning
• Own production reliability across testing, monitoring, versioning, and deployment
• Influence architecture and product decisions while helping shape the technical team as the company scales

• Significant experience building, shipping, and owning ML or LLM systems in production
• Deep technical understanding of modern LLM applications, including retrieval and agentic architectures
• Strong instinct for evaluation and experience developing metrics to understand complex model behaviour
• Strong Python engineering skills with the ability to take ideas from experimentation through to deployed systems
• Experience building reliable production infrastructure around AI or ML systems
• Strong communicator who can work closely across Engineering, Product, and leadership

• Own the technical direction of sophisticated production AI systems
• Solve difficult problems around evaluation, grounding, reliability, and agentic AI
• Make major architectural decisions rather than executing against a predetermined technical roadmap
• Have significant influence across product strategy and the evolution of the technical organization
• Work with proprietary datasets and real-world customer feedback to continuously improve AI performance
• Competitive compensation, meaningful equity, and significant long-term technical progression