Mid-Level AI Engineer

Clera; San Francisco (CA); On-site; USD 150,000 - 180,000; Full time

Job summary

Clera in San Francisco is seeking an experienced software engineer to build production AI systems that automate complex workflows across healthcare, legal, fintech, and more.

You will design agentic multi-step systems, operate retrieval-augmented pipelines, and ship full-stack features from API design to deployment. On-site role with passionate product and design collaboration.

Qualifications

• Two to eight years of software engineering experience.
• Production experience deploying LLM-based services, including prompt design, orchestration, and tool integration.
• Proficiency with Python and TypeScript/React or equivalent, plus cloud platforms such as AWS or GCP and relational or NoSQL databases.
• Working knowledge of RAG, vector databases, embeddings, and retrieval pipelines.
• Experience designing API-driven, high-throughput systems and real-time product features, along with production testing and monitoring.

Responsibilities

• Design and maintain agentic systems for multi-step workflows across areas such as healthcare, legal, fintech, logistics, and compliance.
• Build and operate retrieval-augmented generation pipelines, including vector databases, embeddings, indexing, and domain-specific search.
• Implement multi-agent orchestration, tool calling, memory, and reasoning components.
• Develop evaluations, automated tests, safety measures, and monitoring to track performance and reliability in production.
• Ship full-stack features by designing APIs and data models, writing frontend and backend code, and supporting deployment, CI/CD, and production operations.
• Partner with product and design to set priorities, define success measures, and iterate using user feedback and telemetry.

Skills

Python

TypeScript/React

LLM deployments

APIs

Cloud platforms (AWS/GCP)

Databases (SQL/NoSQL)

RAG pipelines

Agent orchestration

Testing/Monitoring

Production systems

Tools

Vector databases

Embeddings

Indexing

Retrieval pipelines

Tool integration

Job description

About the Role

Join the core product team at an AI recruiting technology company to build production AI systems that automate complex workflows. You will work across the stack to deliver reliable, user-focused products for enterprise and regulated domains.

What You'll Do

• Design and maintain agentic systems for multi-step workflows across areas such as healthcare, legal, fintech, logistics, and compliance.

• Build and operate retrieval-augmented generation pipelines, including vector databases, embeddings, indexing, and domain-specific search.

• Implement multi-agent orchestration, tool calling, memory, and reasoning components.

• Develop evaluations, automated tests, safety measures, and monitoring to track performance and reliability in production.

• Ship full-stack features by designing APIs and data models, writing frontend and backend code, and supporting deployment, CI/CD, and production operations.

• Partner with product and design to set priorities, define success measures, and iterate using user feedback and telemetry.

What We're Looking For

• Two to eight years of software engineering experience delivering user-facing or backend products.

• Production experience deploying LLM-based services, including prompt design, orchestration, and tool integration.

• Proficiency with Python and TypeScript/React or equivalent, plus cloud platforms such as AWS or GCP and relational or NoSQL databases.

• Working knowledge of RAG, vector databases, embeddings, and retrieval pipelines.

• Experience designing API-driven, high-throughput systems and real-time product features, along with production testing and monitoring.

• Experience with agent or workflow frameworks and orchestration tools is useful. Background in multi-tenant enterprise systems or regulated industries is also relevant.

• Familiarity with fine-tuning or multimodal models is a plus.

Compensation & Benefits

Annual salary: $150,000 to $180,000 USD. Visa sponsorship is not available.

Location

On-site in San Francisco, California, United States.