Senior AI Engineer - LLMOps & Agentic AI Systems

Shift Technology; United States; Hybrid; USD 180,000 - 280,000; Full time

Benefits offered by this job

Flexible remote options

Hybrid work model

Generous PTO and holidays

Mental health benefits

Learning & Development opportunities

MAD Days (Make A Difference)

Job summary

Shift Technology in the United States seeks an experienced Lead AI Engineer to drive the LLMOps roadmap and production AI systems within the Data & AI Platform Engineering team. You will lead a small team of engineers, design agentic workflows, and work with product and data science to deliver high-impact AI capabilities.

You will own the ML platform, deploy open-weight models, optimize latency, and promote best practices across validation, instrumentation, and security.

Qualifications

• Proven experience building production agentic systems with strong ML fundamentals.
• Hands-on Python proficiency and experience with experiment tracking and model registry.
• Ability to design robust software systems and lead technical initiatives.

Responsibilities

• Build agentic systems (LLM orchestration, tool calling, MCP, RAG, outputs) and set reference architectures.
• Own LLMOps standards: evaluation harnesses, versioning, tracing, cost governance, release gates.
• Own Databricks-based ML platform integration and CI/CD to serving on AKS; monitor and scale.
• Design and deploy open-weight models with Cloud Ops; optimize latency and throughput.
• Lead and grow a small team, coaching 2–5 engineers and collaborating with product, security, and SRE.

Skills

Agentic AI

Python

LLM orchestration

MLOps

Leadership

English fluency

Cloud platforms

Kubernetes

Terraform

Software design

Education

Bachelor's degree in CS/ML

Tools

Databricks

MLflow

Azure

Kubernetes

Terraform

Job description

Shift Technology in the United States seeks an experienced Lead AI Engineer to drive the LLMOps roadmap and production AI systems within the Data & AI Platform Engineering team. You will lead a small team of engineers, design agentic workflows, and work with product and data science to deliver high-impact AI capabilities.

You will own the ML platform, deploy open-weight models, optimize latency, and promote best practices across validation, instrumentation, and security.