Senior Applied AI Engineer

Clera; San Francisco (CA); On-site; USD 150,000 - 250,000; Full time

Benefits offered by this job

Visa sponsorship

Job summary

Clera seeks an experienced engineer to own the agent infrastructure enabling AI systems to execute tasks reliably, retain context, and involve people when needed. You will build and ship production systems, using real-world feedback to improve planning, recovery, and performance.

You will design memory and retrieval systems, develop evaluation harnesses, and collaborate with customers and teammates to iterate on production agents, orchestration, and reliability. Visa sponsorship is available.

Qualifications

• 3+ years building and shipping LLM agents for production use.
• Strong Python skills and experience building production systems and agent infrastructure.
• Experience developing evaluation harnesses used to inform deployment decisions.
• Hands-on background with memory/context retrieval for operational data and orchestration.”
• Experience implementing failure recovery, retries, or other reliability patterns for agents.
• Experience building agent tools, frameworks, or libraries; production projects from idea to deployment.

Responsibilities

• Own the infrastructure for reliable agent execution across long-running, multi-step tasks.
• Design memory and retrieval systems that preserve context over time.
• Develop evaluation harnesses teams trust for deployment decisions.
• Measure, test, debug, and improve agent systems through development and production lifecycles.
• Collaborate with customers and teammates to iterate on production agents and reliability.

Skills

Python

Production systems

Agent infra

Memory retrieval

Evaluation harnesses

Reliability patterns

Agent tools

Job description

About the Role

Own the agent infrastructure that helps AI systems execute tasks reliably, retain context, and involve people when needed. You will build and ship production systems, using real-world feedback to improve how agents plan, recover, and perform.

What You'll Do

• Build and maintain infrastructure for reliable agent execution across long-running, multi-step tasks.

• Design memory and retrieval systems that work with messy operational data and preserve useful context over time.

• Develop evaluation harnesses that teams can trust when deciding whether to deploy LLM systems.

• Measure, test, debug, and improve agent systems throughout the development and production lifecycle.

• Collaborate with customers and teammates to iterate on production agents, orchestration, and reliability.

What We're Looking For

• At least 3 years of experience building and shipping LLM agents that run unattended in production for real users.

• Strong Python skills and experience building production systems and agent infrastructure.

• Experience developing evaluation harnesses used to inform production deployment decisions.

• Hands-on background with agent memory, context retrieval for operational data, and orchestration or workflow systems.

• Experience implementing failure recovery, retries, or other production reliability patterns for agents.

• Experience building agent tools, frameworks, or libraries; a technical project taken from idea to production is also relevant.

Compensation & Benefits

Base salary of $150,000 to $250,000 USD annually, plus meaningful early equity. Visa sponsorship is available.

Location

On-site in San Francisco, United States.