Principal AI Product Engineer

 

Principal AI Product Engineer

 

What you will be doing:

You will design and implement scalable AI capabilities across our product portfolio, turning advanced models, agents, and conversational interfaces into reusable components that can be embedded across multiple software solutions. Working closely with product, engineering, and data platform teams, you will establish integration patterns for technologies such as conversational AI, RAG, vector search, and model orchestration while leveraging the Databricks platform to build enterprise-ready AI infrastructure. You will also accelerate the delivery of AI-powered features by standardizing infrastructure, creating shared services, and defining governance, monitoring, and evaluation frameworks that ensure AI systems are reliable, secure, and production-ready..

Key Responsibilities

1. Productize AI Capabilities

• Turn models, agents, and conversational interfaces into reusable product capabilities that can be embedded across multiple solutions.

2. Define AI Integration Patterns

• Create scalable patterns for:
• Genie-powered conversational interfaces
• RAG and vector search integration
• Model orchestration and evaluation
• Ensure AI becomes a consistent, trusted layer across products.

3. Accelerate AI Deployment

Reduce time-to-production for AI features by:

• Standardizing infrastructure
• Creating shared services and SDKs
• Defining guardrails and evaluation frameworks
• Enabling faster experimentation without sacrificing governance

4. Architect for Multi-Product Scale

Work deeply in Databricks (Unity Catalog, Delta, Workflows, Model Serving, Genie) to create enterprise-ready AI foundations.

​Required Qualifications

Work Experience:

Years of Applicable Experience - 10 or more years

Education:

Bachelors (Required)

 

Preferred Qualifications

Skills:

Advanced AI/ML engineering, including large language models (LLMs), RAG architectures, agent frameworks, and conversational AI systems

Expertise in the Databricks ecosystem (Unity Catalog, Delta Lake, Workflows, Model Serving, Genie)

Strong backend engineering in Python, including APIs, microservices, and distributed systems design

Experience building and deploying production AI systems, model serving pipelines, and scalable inference architectures

Proficiency with vector databases, embeddings, semantic search, and retrieval frameworks

Full-stack development experience including React, Next.js, TypeScript, and modern frontend frameworks for building AI-driven user interfaces

Experience designing API-first architectures, REST/GraphQL services, and AI-enabled application layers

Experience building shared platforms, SDKs, and internal developer tooling

Strong understanding of cloud-native architectures (AWS, Azure, or GCP).

Knowledge of data engineering and pipeline patterns, including ETL/ELT workflows and large-scale data processing

Experience with AI governance, model evaluation, monitoring, and observability frameworks

Strong understanding of performance, cost, and latency optimization for AI-powered applications

Ability to collaborate across product, data, engineering, and executive leadership to translate AI capabilities into scalable product solutions.

Experience:

• 8+ years engineering experience, including distributed systems
• Deep experience with Databricks platform architecture
• Hands-on experience implementing Genie
• Experience designing RAG pipelines and model-serving architectures
• Strong backend engineering expertise (Python required)
• Experience designing shared services or internal platforms
• Strong understanding of governance, lineage, model evaluation, and AI reliability

Education:

Education

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, or a related technical field required
• Advanced degree (MS or PhD) in AI, Machine Learning, Data Science, or a related discipline preferred
• Equivalent practical experience building and deploying AI-enabled production systems may be considered in place of formal education
• Ongoing engagement with emerging AI technologies, research, and modern engineering practices strongly preferred

 

Additional Job Requirements:

• Remain in a stationary position for prolonged periods of time 

• Be adaptive and change priorities quickly; meet deadlines 

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