Sr. Specialist Solutions Architect

Databricks
Melbourne +1 more
Hybrid

Who this role is best for

Candidates with mid-level ML/AI expertise and a passion for collaboration will find this role's focus on production-grade ML workloads and customer alignment compelling.

Best fit for

  • Mid-level ML engineers with 5+ years of cloud infrastructure experience in production environments
    — “5+ years of hands-on industry ML experience in at least one of the following
  • AI engineers familiar with deploying LLMs and agentic systems using HuggingFace, Langchain, and OpenAI
    — “deploying LLMs with tools such as HuggingFace, Langchain, and OpenAI
  • Individuals who enjoy mentoring and leading technical discussions around MLOps and GenAI
    — “expanding your impact through mentorship, and establishing yourself as an AI thought leader

Things to consider

  • Travel commitment may require up to 30% time away from primary location
    — “Can travel up to 30% when needed
  • Must demonstrate ability to quickly meet technical training and role-specific outcomes
    — “Can meet expectations for technical training and role-specific outcomes within 3 months of hire

How to stand out

  • Highlight experience with end-to-end ML pipelines and cloud-native integration in your resume
    — “Architect production-level ML & AI workloads for customers using our unified platform
  • Emphasize your background with vector databases and AI guardrail systems in interviews
    — “Experience with the latest techniques in LLMs & agentic systems, including vector databases, fine-tuning LLMs, AI guardrail systems
  • Showcase prior mentorship or teaching experience in technical communication
    — “Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · TeamLevel · Senior

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • Architect production-level ML & AI workloads
  • Serve as a trusted practitioner for enterprise GenAI solutions
  • Build, scale, and optimize customer AI workloads
  • Provide advanced technical support to Solution Architects
  • Collaborate cross-functionally with the product and engineering teams
Typical background
5+ years of hands-on industry ML experienceGraduate degree in a quantitative discipline

Skills & requirements

Required

ML EngineerAI EngineerGenaiMlopsCloud InfrastructureDrift MonitoringLlmsAgentic SystemsVector DatabasesFine-tuning LlmsAI Guardrail SystemsDeploying LlmsTechnical SupportCustomer-facing Experience

Preferred

Customer-facing Experience

Stack & domain

ML EngineerAI EngineerGenaiMlopsLlmsAgentic SystemsVector DatabasesFine-tuning LlmsHuggingfaceLangchainOpenaiCommunicationTeachingCollaborationLife-long LearningFinanceHealthcare

About the role

Original posting from Databricks

FEQ427R339

Location: Melbourne or Sydney

As a Specialist Solutions Architect (SSA), you will be the trusted technical ML & AI expert to both Databricks customers and the Field Engineering organization. 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. You will continue to strengthen your technical skills through applying cutting-edge technologies in GenAI, MLOps, and ML more broadly, expanding your impact through mentorship, and establishing 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 a variety of domains

Provide 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

Collaborate 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’ 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 non-technical and technical audiences alike

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

About Databricks

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.

Benefits

At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.

Our Commitment to Diversity and Inclusion

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

Applicant Privacy Notice

Source: Databricks careers

Similar roles