Senior Member of Technical Staff, Agents

Clera

Palo Alto, CA

Remote

Who this role is best for

A natural match if you have experience building evaluation systems for AI products and working in on-site teams.

Best fit for

Candidates with experience in AI evaluation systems and a history of delivering measurable product impact
— “a track record of relevant impact, sustained experience in a role with demonstrated progression”
Individuals who thrive in collaborative, iterative problem-solving environments with a small team
— “collaborative, iterative approach to solving ambiguous problems”

Things to consider

On-site presence required four days per week in Palo Alto, California
— “On-site in Palo Alto, California. The team works in the office four days per week.”
Visa sponsorship is not available, which may limit eligibility for non-US candidates
— “Visa sponsorship is not available.”

How to stand out

Highlight experience in developing evaluation frameworks with measurable success criteria
— “Experience designing evaluation frameworks, including measurable success criteria”
Showcase projects involving large dataset analysis and automated pipelines using Python and SQL
— “Production-quality Python and SQL skills for analysis, large datasets, and automated pipelines.”
Emphasize work on AI systems with a focus on reliability and failure prevention
— “Build agents that complete delegated work end to end, with minimal need for executive oversight.”
Demonstrate ability to create repeatable evaluation workflows for measuring system changes
— “Create repeatable evaluation workflows that let engineers measure the impact of changes.”
Showcase expertise in tools like Django, React, and TypeScript in your technical portfolio
— “Relevant tools and technologies include Python, SQL, Django, React, TypeScript, harness engineering, Braintrust, and Raindrop.”

Pace · Fast PacedCollaboration · MediumAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

successful development of agent capabilities
reliable task completion

Typical background

3+ years in data science or machine learning roles

Skills & requirements

Required

PythonSQLMachine LearningEvaluation SystemsProduction Failures Investigation

Preferred

Autonomous AI CapabilitiesExecutive Productivity

Stack & domain

PythonSQLDjangoReactTypeScriptHarness EngineeringBraintrustRaindropProblem-solvingCommunicationAIMachine Learning

About the role

Original posting from Clera via Ashby

ABOUT THE ROLE
Join a small, fast-moving team building autonomous AI capabilities for executive productivity. You will develop agent capabilities and evaluation systems that help ensure important tasks are completed reliably, and that improvements are proven before reaching users.
WHAT YOU'LL DO
Build agents that complete delegated work end to end, with minimal need for executive oversight.
Define and measure agent quality so the team can confidently assess how often tasks are completed correctly.
Develop new agent capabilities for the tools executives already use, and evaluate readiness before launch.
Investigate production failures, identify underlying causes, and ship fixes that prevent repeat issues.
Build detection systems to surface known failure patterns and unexpected issues at scale.
Improve agent recovery when tools or websites fail.
Create repeatable evaluation workflows that let engineers measure the impact of changes.
WHAT WE'RE LOOKING FOR
At least 3 years in data science or machine learning roles building or delivering evaluation systems, metrics, or quality measurement for products or systems.
Production-quality Python and SQL skills for analysis, large datasets, and automated pipelines.
Experience designing evaluation frameworks, including measurable success criteria, representative datasets, appropriate metrics, and reliable benchmarks.
A track record of relevant impact, sustained experience in a role with demonstrated progression, and a degree from a strong engineering program.
Experience with applied AI or machine learning systems and a collaborative, iterative approach to solving ambiguous problems.
Relevant tools and technologies include Python, SQL, Django, React, TypeScript, harness engineering, Braintrust, and Raindrop.
COMPENSATION & BENEFITS
Base salary: $200,000 to $300,000 annually. Visa sponsorship is not available.
LOCATION
On-site in Palo Alto, California. The team works in the office four days per week.

Source: Clera careers (Ashby)