Applied AI Engineer

This role focuses on building and maintaining intelligent, agent-based systems that support automation and measurable business outcomes. You will take ownership of the end-to-end lifecycle of agent development, including design, versioning, orchestration, and continuous learning, and help bring agentic AI platforms into production.

Role Overview

You will be responsible for delivering scalable Agentic AI platforms that empower developers, improve engineering efficiency, and accelerate organizational AI adoption. The work includes engineering autonomous agents and productionizing AI systems from prototypes.

Responsibilities

• Build scalable Agentic AI platforms that improve engineering efficiency and accelerate AI adoption across the organization.
• Create reusable agent templates and modular components to speed deployment across business units.
• Productionize AI models by transitioning prototypes into production-ready systems.
• Develop autonomous agents and skills for tasks such as code generation and tool calling.
• Optimize model performance to reduce latency and improve reliability.
• Implement prompt engineering strategies, memory handling, resource management, and tool-calling integrations.

Requirements

• 3 to 5+ years of experience in AI/ML engineering and backend development.
• Prior exposure to LLM APIs or AI-powered services in production.
• Experience with AI tools such as LangChain, LlamaIndex, or vector databases.
• Ability to measure and improve model solve rates and accuracy.
• Strong engineering fundamentals including Python and REST.
• Experience with event streaming tools such as Kafka, Flink, Kinesis, or similar, and data pipelines such as Spark, Databricks, or comparable platforms.
• Familiarity with production operations including Kubernetes, CI/CD, monitoring, alerting, and incident response.
• Familiarity with cloud platforms such as AWS, GCP, or Azure, along with REST APIs, Python, and containerization technologies such as Docker and K8s.

Technologies

• Python
• REST APIs
• LLM APIs
• LangChain
• LlamaIndex
• Vector databases
• Kafka, Flink, Kinesis
• Spark, Databricks
• Kubernetes (K8s)
• CI/CD, monitoring, alerting, incident response
• AWS, GCP, Azure
• Docker

Interview AI Use Guidelines

The use of AI or recording tools during live interviews is not permitted unless explicitly invited by the interviewer or approved in advance as part of a reasonable accommodation.

Location & Compensation

• Location: San Jose, CA (onsite)
• Salary: USD 114,100 - 214,950 per year
• Minimum experience: 3 years