Applied AI Engineer
Monte Carlo · Remote · Remote, Americas ·
COMPENSATION
$200k – $260k
Listed on the employer's job board (Ashby)
- Fully remote
- Python + LLMs
- Agent observability
- Series D startup
- 3+ years experience
Join the team building the reliability infrastructure for enterprise AI agents. You will tackle ambiguous problems by researching, prototyping, and shipping agent-powered features like root-cause analysis and incident triage. This role requires owning the full lifecycle, ensuring agents operate safely and effectively in production environments.
What you'll do
- Take open problems from research and prototyping through to production deployment
- Design and ship agent features such as root-cause analysis and monitor generation
- Build evaluation infrastructure including golden datasets and regression suites
- Own retrieval pipelines over customer metadata and instrument agent behavior
- Partner with data science on detection quality and experiment design
- Set technical standards for LLM patterns, guardrails, and internal tooling
What you'll need
- Built autonomous agents in production with real users and internal loops
- Experience running eval frameworks and monitoring non-deterministic agents
- Strong Python skills with a background in ML or data science
- 3+ years in ML, data science, or software engineering at fast-shipping companies
- Comfortable working from ambiguous problem statements rather than strict specs
- Daily use of AI coding assistants for development and research tasks
Nice to have
- Applied statistics and hypothesis testing experience
- Experience building and maintaining MCP servers
- Background in data and cloud space tools like Snowflake or dbt
Stack
- Python
- LLMs
- RAG
- MCP
- Snowflake
- Databricks
- dbt
- Airflow
How you'll work
- Fully remote by design
- Remote-first culture since company inception
What you get
- Competitive compensation package
- Equity ownership
- Recognized as a best workplace for remote teams