Strategic Overview
Sr. Specialist Solutions Architect -AI&ML Engineer at Databricks is a aiml opportunity centered on the specialist responsibilities and outcomes described in the employer's listing.
The published role emphasizes work such as 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. Build, scale, and optimize customer AI….
The role is listed for Israel with the working arrangement published with the role, giving candidates the practical context needed to assess fit before applying.
Key information at a glance
About This Role
FEQ427R400
Mission
As a Sr Specialist Solutions Architect (SSA) - ML & AI Engineer, 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 enterprise and strategic customers in architecting production-grade ML & AI applications on Databricks, while aligning their technical roadmap with the continually evolving Databricks Data…
Key Responsibilities & Objectives
- 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.
- 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
Required Qualifications & Candidate Blueprint
- 7+ years of hands-on industry ML experience in at least one of the following:
- 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
- Experience with data engineering, or a good understanding of the concept of data engineering
Salary & Benefits
The available source data does not publish a numerical salary range for this opening. We do not estimate or substitute third-party figures.
Full Job Description
The following is the complete job description supplied by the source. We sanitize unsafe markup and remove external links, but do not shorten or rewrite the employer's source content.
FEQ427R400
Mission
As a Sr Specialist Solutions Architect (SSA) - ML & AI Engineer, 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 enterprise and strategic 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 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:
- 7+ 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
- Experience with data engineering, or a good understanding of the concept of data engineering
- 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] 5+ 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
- Fluency in Hebrew and English
- Location: Tel Aviv area, with commutable distance to the Databricks office in Herzliya
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.
Editor’s Market Perspective (Our Custom Analysis)
Why This Position Matters
This aiml opening is a useful opportunity for candidates whose experience matches the role-specific capabilities named in the listing. Its strongest career signal is the scope of the work itself — particularly 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. — rather than a generic title alone.
Resume & Application Strategy
For the application, mirror the employer's language where it truthfully matches your background: foreground the role-specific capabilities named in the listing, quantify outcomes from comparable work, and place the most relevant experience near the top of the resume. If the listing specifies tools, platforms, leadership scope, or domain experience, use those exact terms in context instead of presenting an unrelated keyword list.
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