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Specialist Solutions Architect (SSA) - AI/ML Engineering
Specialist Solutions Architect (SSA) - AI/ML Engineering
As a Specialist Solutions Architect (SSA) - AI/ML Engineering, you will be a trusted technical ML & AI expert, guiding customers and the Field Engineering organization in architecting production-grade ML & AI applications on the Databricks platform. You will build, scale, and optimize customer AI workloads, apply best-in-class MLOps, and influence the product roadmap.
About the role
About the Role
As a Specialist Solutions Architect (SSA) - AI/ML Engineering, you will serve as the trusted technical ML & AI expert for both Databricks customers and the Field Engineering organization. You will collaborate with Solution Architects to guide customers in architecting production-grade ML & AI applications on Databricks, ensuring their technical roadmap aligns with the evolving Databricks Data Intelligence Platform. This role offers the opportunity to continuously enhance your technical skills through the application of cutting-edge technologies in GenAI, MLOps, and broader ML, expand your influence through mentorship, and establish yourself as an AI thought leader.
The Impact You Will Have
- Architect production-level ML & AI workloads for customers using our unified platform, including agents, end-to-end ML pipelines, training/inference optimization, integration with cloud-native services, MLOps, etc.
- Serve as a trusted practitioner for enterprise GenAI solutions, including RAG architectures, agentic systems (tool-calling agents, multi-agent orchestration, guardrails), natural language querying of structured data, AI evaluation and observability, and monitoring systems.
- Build, scale, and optimize customer AI workloads and apply best-in-class MLOps to productionize these workloads across various domains.
- Provide advanced technical support to Solution Architects during the technical sale, covering feature engineering, training, tracking, serving, and model monitoring, all within a single platform, while also participating in the larger ML SME community in Databricks.
- Collaborate cross-functionally with the product and engineering teams to represent the voice of the customer, define priorities, and influence the product roadmap, thereby aiding the adoption of Databricks’ AI offerings.
What We Look For
- 5+ years of hands-on industry ML experience in at least one of the following:
- ML Engineer: Build and maintain production-grade cloud (AWS/Azure/GCP) infrastructure that supports the deployment of ML applications, including drift monitoring.
- AI Engineer: Experience with the latest techniques in LLMs & agentic systems, including vector databases, fine-tuning LLMs, AI guardrail systems, and deploying LLMs with tools such as HuggingFace, Langchain, and OpenAI.
- Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience.
- Experience communicating and/or teaching technical concepts to both non-technical and technical audiences.
- Passion for collaboration, life-long learning, and driving business value through ML & AI.
- [Preferred] 2+ years customer-facing experience in a pre-sales or post-sales role.
- Ability to meet expectations for technical training and role-specific outcomes within 3 months of hire.
- Ability to travel up to 30% when needed.