AI Engineer: LLMs & Multi-Agent Orchestration

Auxo Talent; San Francisco (CA); Hybrid; USD 140,000 - 160,000; Full time

Benefits offered by this job

Stock options

Full medical

Dental and vision

401(k)

Paid time off

Job summary

Auxo Talent in the San Francisco Bay Area is hiring a hands-on AI/ML engineer to ship production-grade, LLM-powered systems for critical infrastructure. You will own end-to-end work from data pipelines to agent orchestration, with ownership in a small, fast-moving team.

You'll apply time-series modelling, retrieval-augmented knowledge, and robust testing to deploy reliable AI solutions. This hybrid role offers competitive compensation and equity in a growing company.

Qualifications

• Degree in Computer Science, Machine Learning, Mathematics or similar, or equivalent demonstrated experience.
• Around three years or more of professional AI/ML engineering experience.
• Strong Python, with solid fundamentals across testing, version control and CI/CD.
• Hands-on experience taking LLM APIs into production, not just prototypes.
• Familiarity with agent frameworks and tool/function calling concepts.
• Daily use of AI-assisted coding tools.
• Ability to read ML research and turn it into practical experiments.

Responsibilities

• Multi-agent orchestration and LLM-driven triage workflows.
• Time-series modelling for anomaly detection and failure prediction on multivariate data.
• Retrieval-augmented knowledge systems for operations teams.
• Data and ML pipelines: ingestion, ETL and dataset construction.
• Fine-tuning and post-training of language models for operational use cases.
• Evaluation frameworks, AI observability and production benchmarking.

Skills

Python

CI/CD

AI/ML engineering

Agent frameworks

Testing

Version control

Education

CS/Math degree

Tools

LangChain

PyTorch

Model Serving

Job description

Auxo Talent in the San Francisco Bay Area is hiring a hands-on AI/ML engineer to ship production-grade, LLM-powered systems for critical infrastructure. You will own end-to-end work from data pipelines to agent orchestration, with ownership in a small, fast-moving team.

You'll apply time-series modelling, retrieval-augmented knowledge, and robust testing to deploy reliable AI solutions. This hybrid role offers competitive compensation and equity in a growing company.