GenAI/LLM Engineer for Enterprise Systems (Onsite)

Hygiena; Camarillo (CA); On-site; USD 137,000 - 162,000; Full time

Benefits offered by this job

15 days PTO

10 paid company holidays

Medical with HSA

401(k) with employer contributions

Tuition reimbursement

Charitable contributions matching

Employee referral bonus

Job summary

Hygiena in Camarillo, CA is seeking an Applied AI Engineer (LLM Applications Engineer) to design, build, and deploy production-grade GenAI/LLM solutions across Hygiena products, including SureTrend copilots and workflow automation.

The role requires 3–5 years of software/AI experience, strong Python/API skills, and hands-on work with major LLM platforms, retrieval systems, MLOps, and security testing; you will collaborate with product, data, and safety teams in a regulated domain.

Qualifications

• Bachelor’s degree or equivalent; Master’s preferred.
• 3–5 years of professional software/AI/ML engineering.
• 1+ years building and deploying LLM-powered apps in production.

Responsibilities

• Design, build, and ship GenAI/LLM apps across Hygiena products, including SureTrend copilots and workflow automation.
• Develop advanced retrieval/knowledge systems with grounding to regulatory sources.
• Implement MLOps/LLMOps practices and establish observability and security controls.

Skills

GenAI application delivery

Python proficiency

APIs & services

LLM platforms (Anthropic, Google, Open

Education

Bachelor’s Degree in CS/Data Science/Engineering

Master’s degree a plus

Tools

Claude API/Enterprise

LangChain

LlamaIndex

Vertex AI

Azure ML

Job description

Hygiena in Camarillo, CA is seeking an Applied AI Engineer (LLM Applications Engineer) to design, build, and deploy production-grade GenAI/LLM solutions across Hygiena products, including SureTrend copilots and workflow automation.

The role requires 3–5 years of software/AI experience, strong Python/API skills, and hands-on work with major LLM platforms, retrieval systems, MLOps, and security testing; you will collaborate with product, data, and safety teams in a regulated domain.