Senior Member of Technical Staff

Clera

San Francisco, CA

On-siteCareer-pivot friendly

Who this role is best for

Aimed at experienced engineers with AI and backend expertise who have worked on production systems and startup products.

Best fit for

Experienced engineers with production AI systems and startup product delivery background
— “Substantive startup or founder experience shipping real products”
Candidates with strong retrieval system design and debugging skills in real-world applications
— “Strong retrieval experience, such as knowledge bases, ranking, context validation, or semantic search”
Individuals with multi-step workflow and observability experience in complex pipelines
— “Experience with multi-step workflows, tool orchestration or function calling, and observability or debugging for complex pipelines”

Things to consider

On-site presence in San Francisco is required, limiting remote flexibility
— “On-site in San Francisco, California.”
The role requires managing production failure modes and real-time systems
— “Experience integrating third-party APIs and managing production failure modes”

How to stand out

Highlight experience with model orchestration and prompt engineering in your resume and interviews
— “Experience designing and debugging production AI systems, especially retrieval pipelines, prompt engineering, and model orchestration”
Emphasize your ability to build evaluation frameworks using real data
— “Build evaluation frameworks using real conversations to measure quality and catch regressions”
Showcase your work on multi-step tool workflows and API integration in past roles
— “Create reliable multi-step tool workflows and handle third-party API failures”
Demonstrate your ability to build user-facing controls for non-technical stakeholders
— “Develop interfaces that let non-technical users adjust agent behavior”
Demonstrate experience with optimizing model cost and latency in your application materials
— “Improve speed and cost through model routing, caching, and prompt refinement”

Pace · Fast PacedCollaboration · MediumAutonomy · MediumDecision Impact · Team

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

What success looks like

Build response-generation pipelines
Develop retrieval systems
Create multi-step tool workflows
Implement observability

Typical background

5+ years of professional software engineering experienceExperience building production systems

Skills & requirements

Required

AI SystemsFull-stack DevelopmentProduction SystemsRetrieval SystemsPrompt EngineeringModel OrchestrationObservability

Preferred

Voice IntegrationReal-time SystemsModel Cost Optimization

Stack & domain

AI SystemsFull-stack DevelopmentIntent ClassificationContext AssemblyTool SelectionEscalation DecisionsRetrieval SystemsMulti-step Tool WorkflowsThird-party API IntegrationObservabilityPrompt EngineeringModel OrchestrationKnowledge BasesRankingContext ValidationSemantic SearchReal-time SystemsVoiceModel Cost And Latency OptimizationLeadershipProblem-solvingTeamworkCommunicationInnovationHospitality OperationsAISoftware EngineeringProduction Systems

About the role

Original posting from Clera via Ashby

ABOUT THE ROLE
Join a small engineering team building AI systems for hospitality operations. You will own full-stack components that help AI agents understand guest requests, find reliable information, use tools, and resolve issues or escalate them when needed.
WHAT YOU'LL DO
Build response-generation pipelines for intent classification, context assembly, tool selection, and escalation decisions.
Develop retrieval systems that ground responses in accurate, current customer information.
Create reliable multi-step tool workflows and handle third-party API failures.
Build evaluation frameworks using real conversations to measure quality and catch regressions.
Implement observability and tracing that help support teams understand system behavior.
Develop interfaces that let non-technical users adjust agent behavior.
Extend agent capabilities to voice, including real-time transcription and tool use.
Improve speed and cost through model routing, caching, and prompt refinement, while contributing to infrastructure, data pipelines, integrations, and APIs.
WHAT WE'RE LOOKING FOR
At least 5 years of professional software engineering experience, including 3 or more years building production systems used by real people.
Substantive startup or founder experience shipping real products.
Experience designing and debugging production AI systems, especially retrieval pipelines, prompt engineering, and model orchestration.
Strong retrieval experience, such as knowledge bases, ranking, context validation, or semantic search, plus methods for evaluating production systems.
Experience with multi-step workflows, tool orchestration or function calling, and observability or debugging for complex pipelines.
Proficiency in a backend language such as Python, Go, Rust, or Java, and the ability to work across multiple layers of the stack.
Experience integrating third-party APIs and managing production failure modes; experience with real-time systems, voice, user-facing controls, or model cost and latency optimization is valuable.
COMPENSATION & BENEFITS
Base salary is $130,000 to $220,000 annually, with equity of 0.20% to 1.20%. Benefits include health insurance and a 401(k) match. Visa sponsorship is not available.
LOCATION
On-site in San Francisco, California.

Source: Clera careers (Ashby)