Senior AI Engineer

Jobtailor; California (MO); On-site; USD 120,000 - 190,000; Full time

Job summary

Jobtailor seeks an AI Infrastructure Engineer to design, build, and scale AI tooling that empowers data scientists, engineers and product teams across the organization.

You will develop internal libraries, create integrations with LLM gateways, and contribute to scalable data processing and model serving architectures with strong cloud and containerization expertise.

Qualifications

• Proficiency in Python and ML tooling.
• Experience building infrastructure for engineering and data science teams.
• Experience with ML observability tools (MLflow, Weights & Biases, etc.).
• Understanding of data science workflow from ingestion to deployment and monitoring.
• Experience with cloud environments (AWS, GCP, Azure) and containerization (Docker, Kubernetes).

Responsibilities

• Design, build, and scale AI infrastructure and tooling for data scientists, engineers, and product teams.
• Develop internal tooling and libraries using AI tools and frameworks.
• Create integrations with LLM gateways, agent frameworks, and structured output systems for AI-powered apps.
• Contribute to scalable infrastructure for large-scale data processing and model serving.
• Partner with engineers, data scientists, product, and operations to deliver AI capabilities for real-world use cases.

Skills

Python

Collaboration

ML workflows

Tools

MCP servers/clients

PydanticAI

LangGraph

LiteLLM

Job description

Responsibilities

• Design, build and scale AI infrastructure and tooling that empowers data scientists, engineers and product teams across Shipt
• Develop internal tooling and libraries using AI tools and frameworks
• Create integrations with LLM gateways, agent frameworks, and structured output systems to improve AI-powered applications
• Contribute to the design of scalable infrastructure for large-scale data processing and model serving
• Partner closely with engineers and data scientists and collaborate with product and operations teams to deliver AI capabilities that power real-world logistics, retail and customer experiences

Requirements

• Strong proficiency in Python
• Hands‑on experience building with AI development tools such as MCP servers/clients, PydanticAI, LangGraph, LiteLLM, or similar AI platforms or tools
• Background in developing infrastructure and tooling that supports engineering and data science teams
• Experience with observability and monitoring systems for ML (e.g., MLflow, Weights & Biases, or similar)
• Solid understanding of the data science workflow, from data ingestion and feature engineering to experimentation, deployment, and monitoring
• Experience with cloud environments (AWS, GCP, or Azure) and containerized development (Docker, Kubernetes)
• Have an AI first mindset and passion, with curiosity to learn and leverage AI in all aspects of your work
• Strong collaboration skills