Agent Engineer

Clera

Palo Alto, CA

Remote

Who this role is best for

Experienced software engineers with full-stack capabilities and agent system expertise will find this role in AI-powered productivity software development rewarding. The on-site requirement and emphasis on building reliable agent systems indicate a preference for seasoned professionals with a strong technical foundation.

Best fit for

Experienced full-stack engineers with a background in AI agent development and system integration
— “Build and evolve Python agent systems, including orchestration, context management, retries, and error recovery.”
Candidates who have operated production systems and optimized for reliability and performance
— “Improve latency, cost, reliability, and safety in high-volume agent execution.”
Individuals with a proven ability to design reusable platform abstractions and workflows
— “Create platform abstractions that make capabilities easier to compose, extend, and maintain.”

Things to consider

On-site presence in Palo Alto is mandatory, which may be a constraint for remote candidates
— “On-site in Palo Alto, United States.”
Visa sponsorship is not available, so non-US candidates may need to explore other options
— “Visa sponsorship is not available.”

How to stand out

Showcase your track record in building and operating end-to-end production systems
— “At least 5 years of experience building and operating production software systems end to end.”
Emphasize your experience with API integrations and debugging across multiple layers of a system
— “Experience debugging across prompts, model outputs, application code, databases, and APIs.”

Pace · Fast PacedCollaboration · MediumAutonomy · HighDecision Impact · Individual

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

What success looks like

reliable agent systems
improved latency

Typical background

software engineeringAI development

Skills & requirements

Required

PythonDjangoReactApis

Preferred

LlmsPrompt Engineering

Stack & domain

PythonDjangoApisReactTypeScriptLlmsModel EvaluationPrompt EngineeringDistributed SystemsLatency OptimizationCost OptimizationReliability OptimizationError RecoveryEmail IntegrationCalendar IntegrationMessaging IntegrationBrowser IntegrationDocument IntegrationCRM IntegrationProduction OperationsPlatform AbstractionsProblem-solvingCommunicationTeamworkAdaptabilityLeadershipAIProduct DevelopmentSoftware Engineering

About the role

Original posting from Clera via Ashby

ABOUT THE ROLE
Join an AI-powered productivity software team building dependable agent capabilities for real-world work. You will help turn advances in reasoning, planning, memory, and tool use into useful product experiences that users can trust.
WHAT YOU'LL DO
Explore advances in agent technology and identify opportunities to solve user problems.
Translate model capabilities into reliable, reusable skills and workflows.
Build and evolve Python agent systems, including orchestration, context management, retries, and error recovery.
Design integrations with email, calendars, messaging, browsers, documents, CRMs, and other business software.
Own capabilities across Python services, Django, APIs, React interfaces, data models, background jobs, and production operations.
Create platform abstractions that make capabilities easier to compose, extend, and maintain.
Improve latency, cost, reliability, and safety in high-volume agent execution.
Use evaluations, production traces, and user feedback to find and fix quality issues.
Set technical direction for ambiguous problems and contribute to design reviews.
WHAT WE'RE LOOKING FOR
At least 5 years of experience building and operating production software systems end to end.
Strong Python skills and experience with Django, APIs, React, and TypeScript.
Hands-on experience with agent systems, including planning, tool calling, structured outputs, context and state management, retries, and orchestration.
Experience building external API and business software integrations.
Ability to turn loosely defined user needs into clear product capabilities and reusable system abstractions.
Experience debugging across prompts, model outputs, application code, databases, and APIs, and using production signals to guide improvements.
Background in LLMs, model evaluation, or prompt engineering in production is valuable, as is experience optimizing distributed systems for latency, cost, and reliability.
A degree from a strong engineering program, plus startup experience or a demonstrated record of career progression.
COMPENSATION & BENEFITS
Visa sponsorship is not available.
LOCATION
On-site in Palo Alto, United States.

Source: Clera careers (Ashby)