# Sr. Specialist Solutions Architect

**Company**: Databricks
**Location**: Melbourne, Australia
**Work arrangement**: hybrid
**Experience**: senior
**Job type**: full-time
**Category**: Engineering
**Industry**: Technology
**Wikidata**: https://www.wikidata.org/wiki/Q18350420

**Apply**: https://job-boards.greenhouse.io/databricks/jobs/8625656002?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_9423bcd5-8f1

## Description

As a Specialist Solutions Architect (SSA), you will be the trusted technical ML & AI expert to both Databricks customers and the Field Engineering organisation.

You will work with Solution Architects to guide customers in architecting production-grade ML & AI applications on Databricks, while aligning their technical roadmap with the continually evolving Databricks Data Intelligence Platform.

The impact you will have:

- Architect production-level ML & AI workloads for customers using the unified platform, including agents, end-to-end ML pipelines, training/inference optimisation, integration with cloud-native services, MLOps, etc.

- Serve as a trusted practitioner for enterprise GenAI solutions, including RAG architectures, agentic systems, natural language querying of structured data, AI evaluation and observability, and monitoring systems.

- Build, scale, and optimise customer AI workloads and apply best-in-class MLOps to productionise these workloads across various domains.

- Provide advanced technical support to Solution Architects during the technical sale, ranging from feature engineering to model monitoring.

- Collaborate cross-functionally with product and engineering teams to represent the voice of the customer and influence the product roadmap.

What we look for:

- 5+ years of hands-on industry ML experience in at least one of the following: ML Engineer, 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 or equivalent practical experience.

- Experience communicating technical concepts to 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.

- Can meet expectations for technical training and role-specific outcomes within 3 months of hire.

- Can travel up to 30% when needed.

## Skills

### Required
- ML Engineer
- AI Engineer
- LLMs
- agentic systems
- vector databases
- fine-tuning LLMs
- AI guardrail systems
- HuggingFace
- Langchain
- OpenAI
- MLOps
- cloud-native services

### Nice to have
- customer-facing experience
- pre-sales experience
- post-sales experience

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Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/databricks/jobs/8625656002?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)