- Job title
- Product Analyst
- Job location
- San Francisco, CA, US
- Job description
- ### About DynamoAI
Dynamo AI is building the future of trustworthy AI for the enterprise. Our platform provides real-time guardrails, redteaming, and observability for generative AI systems—ensuring safe, compliant, and reliable AI deployments in regulated industries such as financial services, insurance, DoD, and healthcare.
### The role
PMs run several workstreams at once. As an analyst, you take individual complex items inside those streams and own their design and specification: scope the problem, design the experiment, define how success is measured, run the analysis, and come back with a recommendation. When building is faster than waiting, that includes standing up a quick custom tool with AI to test an idea.
You won't write training or infrastructure code; the platform handles that. What you bring is experimental design and analytical rigor.
### What you might work on
* **Guardrail training data**: curate and design the data that trains an SLM guardrail (for example, a prompt injection detector), and keep labeling consistent as datasets grow.
* **Orchestration experiments**: test different configurations of guardrails and controls against each other to find what performs best.
* **Synthetic data quality**: assess whether synthetic training or eval data is faithful and diverse enough to trust.
* **New evaluations**: research and scope new ways to evaluate guardrails and AI applications, then specify how they work.
* **Rapid tooling**: build small custom tools with AI to validate a hypothesis or unblock the team.
* **Benchmarking**: measure performance with standard classification metrics (FNR, FPR, precision, recall) and report what's working and what isn't.
### Growth path
You'll start on well-scoped items and move to harder, more ambiguous ones. Over time you'll build intuition for SLM training, guardrail orchestration, and how controls fit into a full AI application. This is a track toward a senior, technical product role.
### Requirements
* A degree with strong quantitative or analytical content. We're especially interested in less common backgrounds (physics, information or data theory, business, and similar) alongside solid data-analysis experience.
* A clear, demonstrated framework for thinking through problems.
* Good instinct for data, ML concepts, and what makes an experiment or metric trustworthy.
* Python and pandas for working with data.
* Interest in AI security or safety and adversarial thinking.
* Attention to detail and clear writing.
### Nice to have
* ML coursework.
* Reading or working proficiency in Japanese, Chinese, or a European language.
* Coursework or projects in stats or NLP.
* SQL.
* A habit of building small tools or scripts (including with AI assistants) to answer your own questions.
* Exposure to LLMs, security tooling, experimental design, or annotation work.
