AI Engineer

San Francisco, California

Software Engineering

Permanent

Our client, an exciting HealthTech organization, are hiring an AI Engineer to join the team in New York. The successful candidate will lead the architecture, development and deployment of Agentic AI and production-grade LLM applications, as well as design intelligent, scalable and resilient AI-based systems that drive real impact, transforming clinical and scientific workflows.

Responsibilities

Design and architect agentic AI systems that address complex, real-world problems with clarity and precision.
Lead the development of advanced prompting strategies and drive prompt engineering for production use.
Make strategic decisions on model selection, workflow orchestration and system optimization.
Establish and promote best practices for AI system reliability, observability and performance.
Develop and maintain LLM-powered applications using modern Python frameworks.
Build robust, asynchronous task-handling systems leveraging technologies like SQS and Redis.
Architect fault-tolerant systems to handle LLM unpredictability and service disruptions gracefully.
Mentor and guide engineers on AI architecture, agentic design and production tooling.
Lead the adoption of emerging AI frameworks and tools across the organization.
Play a key role in defining the AI roadmap and shaping the long-term technical direction.

Skillset

PhD in Computer Science, Machine Learning or similar with at least 5 years of experience building, deploying and scaling production-grade AI/ML applications.
Proven expertise in advanced prompt engineering and deploying LLM workflows in production environments.
In-depth knowledge of agentic AI patterns and orchestration frameworks.
Hands-on experience managing LLM operations, including deployment, scaling and lifecycle management.
Strong command of modern Python, including asyncio, FastAPI and related frameworks.
Familiarity with agentic and LLM tools such as LangGraph, PydanticAI or equivalent.
Experience working with leading foundation models, including Claude, GPT-4 and others.
Solid understanding of distributed systems, asynchronous processing and queuing technologies (e.g. SQS, Redis).
Deep interest in applying AI to solve real-world challenges in healthcare and life sciences.
Excellent written and verbal communication skills, with the ability to convey complex ideas clearly.