Sr. AI Engineer - Forward Deployed Engineer Senior Manager· Databricks · Reinvention Centers
About The Position
The Advanced Technology Centers (ATCs) are the engine for reinvention in our clients’ transformation journey. Powered by more than 255,000 people across 24 countries, ATCs provide our clients with seamless access to industry insights and innovative technology solutions. The Advanced Technology Centers (ATCs) make a tremendous impact in solving our clients’ business problems by leveraging innovation, intelligence, industry insights, new IT, and new technology skills. As a Network, ATCs are positioned to unlock greater opportunities and exponential value for our clients. For our clients, the Network provides the strength of our geographic diversity, greater resilience, and seamless access to the deepest industry knowledge, the latest in Gen AI solutions, and tech expertise from around the world. For our people, it brings an opportunity to shape truly boundaryless career paths in a highly collaborative team of experts where they can learn from each other and solve the world’s most complex client challenges. You are a Senior AI Native Engineer who builds, leads, and scales world-class AI/ML professional services on the Databricks Intelligence Platform. You develop executive relationships with VP+, CIO, and CDO stakeholders as a trusted advisor on complex AI transformations, align with Field Engineering and Sales Leaders on strategic accounts, and shape cross-functional influence across Product, R&D, and GTM. You lead AI PS initiatives, design reusable engagement models for global repeatability, own OKRs for AI-services led accounts, and represent Databricks as a thought leader in AI/ML.
Requirements
- Minimum 10 years of experience on Databricks and large-scale big data projects (Delta Lake, DLT, Apache Spark, Unity Catalog).
- You've also built API layers that expose data and AI/ML capabilities to enterprise systems.
- Minimum 10 years of experience in Python, Java, or equivalent.
- Comfortable with evaluation tooling, logging, monitoring, and observability.
- Minimum 10 years of experience deploying and operating production systems with CI/CD, infrastructure as code, and observability tooling.
- Practical MLOps and LLMOps experience: CI/CD across the ML and LLM lifecycle covering model training, evaluation harnesses, model serving, monitoring, and prompt management.
- Minimum 1 year experience in designing and shipping agentic AI solutions in production.
- Minimum 1 year of experience with agentic orchestration tools (LangGraph, CrewAI, AutoGen, or similar).
- Hands on with Databricks AI tooling: Mosaic AI, Vector Search, Model Serving, MLflow, and Unity Catalog governance.
- You've built RAG and multi-agent systems on the Databricks Intelligence Platform.
- Minimum 1 year experience working with AI platforms across OpenAI, Claude, Vertex AI, and open-source models.
- Bachelor's degree or equivalent (minimum 12 years) work experience. (If Associate Degree, must have minimum 6 years work experience)
Responsibilities
- Design and engineer enterprise-ready AI agents encompassing retrieval, orchestration, policy-based routing, tool invocation, evaluation harnesses, and lifecycle observability.
- Architect AI-native solutions on Databricks (Mosaic AI, Vector Search, Model Serving, MLflow) with Unity Catalog governance, scaling reusable patterns across customer engagements.
- Establish Lakehouse data foundations (Delta Lake, DLT, Unity Catalog) that power production AI across customer portfolios.
- Develop abstraction layers across AI providers (Anthropic, Google, OpenAI, etc.) to enable seamless integration.
- Leverage containerization, microservices, serverless, and event-driven architectures to deliver scalable AI-native systems.
- Tailor and deploy agentic applications across industries such as finance, healthcare, and retail.
- Conduct design workshops, proofs of concept, and code-with sessions with client stakeholders.
- Define and use metrics to measure agent accuracy, latency, safety, and cost effectiveness.
- Process large-scale distributed datasets on the Databricks Intelligence Platform with Apache Spark™.
- Integrate LLM solutions with APIs, model monitoring, and prompt management.
- Operate MLOps / LLMOps pipelines with CI/CD across the ML and LLM lifecycle.
Benefits
- medical, dental, vision, life, and long-term disability coverage
- a 401(k) plan
- bonus opportunities
- paid holidays
- paid time off
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
