AI Engineer (LLM / Agentic Systems)

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

Bay Area, California | Hybrid | $140,000 to $160,000 + equity

A well-funded early stage company is applying AI to the operational side of critical infrastructure. Their platform pulls live data from sensor and control networks across large facilities, then uses agentic AI to spot problems, connect related events and give operators recommendations in real time. It is a genuinely hard technical problem in a market that is growing quickly.

This suits an engineer with roughly three to six years behind them who has already shipped LLM-powered systems into production and wants more ownership than a large team allows. You would be joining a small engineering group and working end to end, from data pipelines and model integration through to agentic orchestration, evaluation and production support.

It is not a research role, but research thinking matters. You will be expected to keep up with the field, bring ideas forward and then build them properly.

What you will work on

• 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

What you will need

• 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 agentic concepts such as tool and function calling, and agent frameworks
• Daily use of AI-assisted coding tools
• Ability to read ML research and turn it into practical experiments

Nice to have

• LangGraph, LangChain or similar agent frameworks, MCP a plus
• Time-series forecasting and anomaly prediction
• Fine-tuning or post-training experience
• PyTorch and model serving frameworks
• LLM evaluation and benchmarking, harness design
• Exposure to industrial or building control systems
• Background in DevOps, distributed systems or observability tooling

On offer

$140,000 to $160,000 base, stock options, full medical, dental and vision, 401(k) and paid time off.