<?xml version="1.0" encoding="UTF-8"?>
<source>
  <jobs>
    <job>
      <externalid>10ceb713-2cf</externalid>
      <Title>Specialist Solutions Architect - AI &amp; ML (Financial Services)</Title>
      <Description><![CDATA[<p>As a Specialist Solutions Architect - AI &amp; ML Engineer, you will be the trusted technical ML &amp; AI expert to both Databricks customers and the Field Engineering organization.</p>
<p>You will work with Solution Architects to guide customers in architecting production-grade ML &amp; AI applications on Databricks, while aligning their technical roadmap with the continually evolving Databricks Data Intelligence Platform.</p>
<p>Your responsibilities will include:</p>
<ul>
<li>Architecting production-level ML &amp; 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.</li>
</ul>
<ul>
<li>Serving 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</li>
</ul>
<ul>
<li>Building, scaling, and optimizing customer AI workloads and applying best-in-class MLOps to productionize these workloads across a variety of domains</li>
</ul>
<ul>
<li>Providing advanced technical support to Solution Architects during the technical sale ranging from feature engineering, training, tracking, serving to model monitoring all within a single platform, as well as participating in the larger ML SME community in Databricks</li>
</ul>
<ul>
<li>Collaborating cross-functionally with the product and engineering teams to represent the voice of the customer, define priorities and influence the product roadmap, helping with the adoption of Databricks&#39; AI offerings</li>
</ul>
<p>We are looking for someone with 5+ years of hands-on industry ML experience in at least one of the following areas:</p>
<ul>
<li>ML Engineer: Build and maintain production-grade cloud (AWS/Azure/GCP) infrastructure that supports the deployment of ML applications, including drift monitoring.</li>
</ul>
<ul>
<li>AI Engineer: Experience with the latest techniques in LLMs &amp; agentic systems including vector databases, fine-tuning LLMs, AI guardrail systems, and deploying LLMs with tools such as HuggingFace, Langchain, and OpenAI</li>
</ul>
<p>A graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience is also required.</p>
<p>Additionally, experience communicating and/or teaching technical concepts to non-technical and technical audiences alike is highly valued.</p>
<p>The salary range for this position is $180,000-$247,500 USD, depending on location.</p>
<p style="margin-top:24px;font-size:13px;color:#666;">XML job scraping automation by <a href="https://yubhub.co">YubHub</a></p>]]></Description>
      <Jobtype>full-time</Jobtype>
      <Experiencelevel>senior</Experiencelevel>
      <Workarrangement>remote</Workarrangement>
      <Salaryrange>$180,000-$247,500 USD</Salaryrange>
      <Skills>ML Engineer, AI Engineer, GenAI, MLOps, Cloud Native Services, Vector Databases, Fine-Tuning LLMs, AI Guardrail Systems, HuggingFace, Langchain, OpenAI</Skills>
      <Category>Engineering</Category>
      <Industry>Technology</Industry>
      <Employername>Databricks</Employername>
      <Employerlogo>https://logos.yubhub.co/databricks.com.png</Employerlogo>
      <Employerdescription>Databricks is a data and AI company that provides a unified platform for data, analytics, and AI.</Employerdescription>
      <Employerwebsite>https://databricks.com</Employerwebsite>
      <Compensationcurrency></Compensationcurrency>
      <Compensationmin></Compensationmin>
      <Compensationmax></Compensationmax>
      <Applyto>https://job-boards.greenhouse.io/databricks/jobs/8434243002</Applyto>
      <Location>Central - United States; Northeast - United States; Southeast - United States</Location>
      <Country></Country>
      <Postedate>2026-04-18</Postedate>
    </job>
  </jobs>
</source>