Job Summary
Are you ready to make a significant impact in the tech world? We are on the hunt for a Principal AI Engineer who thrives on pushing boundaries and architecting next-generation AI platforms. As a strategic technical leader on our team, you'll be at the helm of designing, developing, and deploying enterprise-grade AI applications, real-time agentic workflows, and complex data-driven reasoning platforms that scale effortlessly across global workloads.
Our tech stack is as versatile as it is powerful, featuring Python, Java, DataFlow, BigQuery, BigTable, Pub/Sub, Kubernetes, Vector Search Engine infrastructure, and enterprise AI orchestration frameworks—all natively integrated within the Google Cloud Platform (Vertex AI, GKE, Dataflow).
This isn't just another coding job—this is your opportunity to define the long-term technical vision of our enterprise AI strategy, set standards for autonomous agent systems, and drive game-changing architectural transformations. You'll lead high-stakes technical directions, establish enterprise-wide AI design patterns, and mentor engineering teams across the organization. We're looking for visionary tech leaders and lifelong learners who are eager to bridge the gap between advanced AI capabilities and mission-critical production systems.
In our fast-paced, high-energy environment, cross-functional leadership is paramount. You'll collaborate closely with executive leadership, product leaders, security directors, and cross-functional engineering teams to turn ambitious AI initiatives into transformative, reliable products.
Your Impact
•Architectural Leadership: Define and execute the technical strategy for enterprise AI, LLM deployment architectures, and multi-agent systems across the engineering organization.
•Agentic & Reasoning Systems: Design scalable multi-agent systems, autonomous decisioning engines, tool-use frameworks, and complex event-driven agentic workflows.
•Data & AI Infrastructure: Architect end-to-end streaming and batch data/embedding pipelines, hybrid search/RAG architectures, and vector indexing systems powering enterprise LLM features.
•Production Guardrails & Governance: Set enterprise standards for AI evaluation, observability, cost-performance optimization, safety guardrails, hallucination reduction, and security compliance.
•Technical Excellence: Mentor Senior Staff and Senior Engineers, establish code quality standards, and foster a culture of continuous AI innovation and research-to-production execution.
•Cross-Functional Influence: Partner with Product, Security, and Cloud Architecture teams to align technology roadmaps with long-term business goals.
Qualifications
•Experience: 9+ years of software engineering experience with 4+ years of hands-on experience designing and delivering production-grade AI/LLM features, RAG platforms, and agentic architectures.
•GCP & Cloud Native: Extensive hands-on experience with Google Cloud Platform (GCP) services, including Vertex AI, BigQuery, DataFlow, BigTable, and GKE.
•Agentic Orchestration & AI Frameworks: Deep expertise with modern agentic architectures (multi-agent orchestration, human-in-the-loop controls, task planning, state management, long-term memory systems) using frameworks like LangChain/LangGraph, LlamaIndex, AutoGen, or custom agent engines.
•Data Engineering & Vector Search: Proven background in data engineering, building streaming/batch pipelines (DataFlow, Apache Beam, Spark), and fine-tuning vector search architectures (Vertex AI Vector Search, Pinecone, PGVector, Milvus).
•Core Languages: Mastery in Python and Java/Scala with a strong focus on high-throughput, latency-sensitive, and fault-tolerant system design.
•Streaming & Messaging: Expert knowledge of distributed event streaming platforms (Google Pub/Sub, Kafka) and asynchronous event-driven system architecture.
•DevOps, MLOps & CI/CD: Hands-on experience with MLOps/LLMOps pipelines, continuous evaluation CI/CD (Jenkins, GitLab CI/CD, Vertex AI Pipelines), model monitoring, tracing (LangSmith, Phoenix, OpenTelemetry), and deployment patterns.
•Security & Governance: Deep understanding of data privacy, prompt injection prevention, access control, encryption, and governance in enterprise cloud AI environments.
•Containerization: Advanced knowledge of Kubernetes (GKE), service meshes, and microservices architecture.
•Location: Must be located in the SF Bay Area for on-site collaboration.
Compensation Disclosure
The compensation offered for this position will depend on qualifications, experience, and work location. For candidates who receive an offer at the posted level, the starting base salary (for non-sales roles) or base salary + commission target (for sales/commissioned roles) is expected to be the annual range listed below. The offered compensation may also include restricted stock units and a bonus.
$156,400.00 - $253,000.00/yr
Is role eligible for Immigration Sponsorship?: Yes
