Agent Engineer

Wwshemi; Palo Alto (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

Wwshemi is seeking an experienced software engineer to build and scale agent-enabled product experiences in Palo Alto. You will own Python-based agent infrastructure, integrate Django services and React interfaces, and drive performance, reliability, and observability across production systems.

The role requires at least 5 years building end-to-end systems, strong Python and API skills, and a track record in designing reusable platform abstractions. Hybrid on-site work in Palo Alto is offered.

Qualifications

• 5+ years building production software end-to-end, incl. deployment and operations.
• Strong Python skills with Django, APIs, React, and TypeScript.
• Experience building or operating agent systems: planning, tool calls, structured outputs, context/state management, retries, orchestration.
• Experience designing integrations with external APIs and business software.
• Ability to turn loosely defined user needs and new tech into practical product features.
• Experience owning complex production systems: observability, debugging, and improvements from production signals.
• Design reusable platform abstractions and diagnose issues across prompts, model outputs, app code, databases, APIs.
• Background in LLMs, prompt engineering, or production model eval; optimizing high-volume systems for latency, cost, reliability.
• Career progression or startup founding experience, with strong engineering fundamentals.

Responsibilities

• Investigate developments in agent technology and identify valuable product opportunities.
• Translate model behaviors into reusable skills and workflows addressing user needs.
• Build and improve Python agent infrastructure: orchestration, context management, outputs, retries, error recovery.
• Own capabilities across Python agents, Django services, APIs, React interfaces, data models, background jobs, observability, and production ops.
• Create platform abstractions to make capabilities easier to compose, extend, and maintain.
• Improve agent execution latency, cost, reliability, and safety.
• Work with evaluation/quality partners to define behavior and turn results into improvements.
• Analyze production traces and user feedback to identify and resolve issues.
• Guide technical decisions and contribute to design reviews.

Skills

Python

Django

APIs

React

TypeScript

Agent systems

End-to-end production

Tools

APIs

React

TypeScript

Job description

Employment Full-time

Build reliable agent capabilities that turn advances in reasoning, planning, memory, and tool use into useful product experiences. This role spans agent systems, platform engineering, integrations, and full-stack product development.

What You'll Do

• Investigate developments in agent technology and identify valuable product opportunities.
• Translate promising model behaviors into reusable skills and workflows that address user needs.
• Build and improve Python agent infrastructure, including orchestration, context management, structured outputs, retries, and error recovery.
• Own capabilities across Python agents, Django services, APIs, React interfaces, data models, background jobs, observability, and production operations.
• Create platform abstractions that make capabilities easier to compose, extend, and maintain.
• Improve agent execution latency, cost, reliability, and safety.
• Work with evaluation and quality partners to define expected behavior and turn evaluation results into engineering improvements.
• Analyze production traces and user feedback to identify and resolve underlying issues.
• Guide technical decisions on ambiguous problems and contribute to design reviews.

What We're Looking For

• At least 5 years of experience building production software systems end to end, including deployment and operational iteration.
• Strong Python skills and hands-on experience with Django, APIs, React, and TypeScript.
• Experience building or operating agent systems, including planning, tool calling, structured outputs, context and state management, retries, and orchestration.
• Experience designing integrations with external APIs and business software.
• Ability to turn loosely defined user needs and emerging technologies into practical product features.
• Experience owning complex systems in production, including observability, debugging, and improvements based on production signals.
• Skill in designing reusable platform abstractions and diagnosing issues across prompts, model outputs, application code, databases, and APIs.
• Background in LLMs, prompt engineering, or production model evaluation is useful, as is experience optimizing high-volume systems for latency, cost, and reliability.
• Demonstrated career progression within an organization or experience founding a startup, along with strong engineering fundamentals.

Location

On-site in Palo Alto, California, with hybrid flexibility.