Artificial Intelligence Engineer

About the role

Role: Artificial Intelligence Engineer (26-03359)

Location: Palo Alto, CA 94306 - Hybrid Model - three days per week

Duration: Full Time

Job Description:

We are seeking an AI Engineer with strong backend skills to design, build and scale AI driven capabilities. The role focuses on building robust AI systems, developing the surrounding LLM harness and quality frameworks, leveraging advanced GenAI techniques, and implementing production monitoring for end-to-end delivery in a fast-paced environment. This opportunity is heavily focused on backend and GenAI work.

Responsibilities:

Design, implement and optimize backend services that support AI workflows.

Integrate ML and LLM models into production systems with focus on performance, reliability and scalability.

Building and owning AI features end to end.

Evaluating/monitoring AI systems in pre-release/production environments.

Building reliable AI systems and writing production code.

Experience building or maintaining backend services or microservices.

Diagnose complex issues across data pipelines, model serving and backend components. This role focuses on building active APIs, microservices, and real-time serving infrastructure. It is not a Data Engineering role focused on ETL or batch processing pipelines.

Collaborate with product and cross functional teams to refine requirements and translate them into clear technical plans.

Contribute to system design, architecture reviews and code quality improvements.

Support innovation and continuous improvement by identifying opportunities and driving technical initiatives.

Qualifications:

4+ years of backend engineering experience in Python, Go, Java or similar.

Familiarity with evaluating model performance using metrics.

Proven experience building high performance or distributed systems.

4+ years of hands on experience integrating ML or LLM models into production.

Strong understanding of cloud infrastructure, microservices and observability.

Ability to operate effectively under ambiguity and navigate dynamic environments.

Strong communication and collaboration skills.

Hybrid Work Model: This role supports a flexible hybrid work model, requiring a minimum of three days per week on-site in the office, per company policy.