Databricks

1 week ago

Senior Specialist Solutions Architect (AI/ML)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 hour agoStatus: Live

Job Summary

Serve as Databricks’ trusted technical expert for ML and AI, partnering with customers and Field Engineering to design production-grade AI applications on the Data Intelligence Platform. Architect end-to-end ML/AI workloads, lead enterprise GenAI initiatives (including RAG and agentic systems), and provide advanced technical support during the sales cycle with MVPs and deep dives. Collaborate with product and engineering to shape the AI roadmap while mentoring peers and driving adoption through tutorials, training, conferences, and hackathons.

Location: London

Workplace: Onsite

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Seniority: Mid level

Key Responsibilities

•Architect and implement production-level ML and AI workloads, including end-to-end pipelines, training/inference optimization, MLOps lifecycle management, and integration with cloud-native services.
•Lead enterprise GenAI solutions, specializing in RAG architectures, agentic systems (tool-calling, multi-agent orchestration, guardrails), AI observability, and natural language querying of structured data.
•Provide advanced technical support to Solution Architects during the technical sales cycle by building MVPs, leading deep-dive sessions, and aligning AI solutions to customer business challenges.
•Collaborate cross-functionally with product and engineering teams to represent the customer voice, define priorities, and influence the platform’s AI roadmap.
•Drive thought leadership and community adoption through technical tutorials and training materials, presenting at industry conferences, and leading hackathons.

Travel: Medium travel

Key Requirements

•10+ years of hands-on industry DS/ML experience focused on either ML engineering (production ML platforms on cloud) or data science/AI (LLMs, agentic systems, vector databases, fine-tuning).
•Hands-on experience with distributed Spark-based systems and a strong understanding of data engineering concepts.
•Pre-sales or post-sales experience supporting external clients across industries, with preference for 5+ years of customer-facing experience.
•Proven ability to communicate and teach complex technical concepts to technical and non-technical audiences.
•Graduate degree in a quantitative discipline (e.g., Computer Science, Engineering, Statistics, Operations Research) or equivalent practical experience.

Experience:10+ yearsData scienceMachine learningAILLMsGenAIMLOpsDistributed systemsCustomer-facing

Education:High School

Skills:CommunicationTeachingCollaborationLifelong learningDriving business value

Languages:English

Tech Stack:Data Intelligence PlatformGenAILLMRAGAgentic systemsTool-callingMulti-agent orchestrationGuardrailsAI observabilityNatural language queryingMLOpsLLMOpsAWSAzureGCPHuggingFaceLangChainVector databasesFine-tuningSpark

Company Brief

Databricks

Provides a unified data analytics platform powered by Apache Spark to simplify building, deploying, and scaling data engineering, data science, and machine learning workloads for enterprises.

Industry: Data Infrastructure

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series E+

Headquarters: San Francisco, United States

Founded: 2013

Website LinkedIn

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Databricks

1 week ago

Senior Specialist Solutions Architect (AI/ML)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 hour agoStatus: Live

Job Summary

Location: London

Workplace: Onsite

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Seniority: Mid level

Key Responsibilities

•Architect and implement production-level ML and AI workloads, including end-to-end pipelines, training/inference optimization, MLOps lifecycle management, and integration with cloud-native services.
•Lead enterprise GenAI solutions, specializing in RAG architectures, agentic systems (tool-calling, multi-agent orchestration, guardrails), AI observability, and natural language querying of structured data.
•Provide advanced technical support to Solution Architects during the technical sales cycle by building MVPs, leading deep-dive sessions, and aligning AI solutions to customer business challenges.
•Collaborate cross-functionally with product and engineering teams to represent the customer voice, define priorities, and influence the platform’s AI roadmap.
•Drive thought leadership and community adoption through technical tutorials and training materials, presenting at industry conferences, and leading hackathons.

Travel: Medium travel

Key Requirements

•10+ years of hands-on industry DS/ML experience focused on either ML engineering (production ML platforms on cloud) or data science/AI (LLMs, agentic systems, vector databases, fine-tuning).
•Hands-on experience with distributed Spark-based systems and a strong understanding of data engineering concepts.
•Pre-sales or post-sales experience supporting external clients across industries, with preference for 5+ years of customer-facing experience.
•Proven ability to communicate and teach complex technical concepts to technical and non-technical audiences.
•Graduate degree in a quantitative discipline (e.g., Computer Science, Engineering, Statistics, Operations Research) or equivalent practical experience.

Experience:10+ yearsData scienceMachine learningAILLMsGenAIMLOpsDistributed systemsCustomer-facing

Education:High School

Skills:CommunicationTeachingCollaborationLifelong learningDriving business value

Languages:English

Company Brief

Databricks

Provides a unified data analytics platform powered by Apache Spark to simplify building, deploying, and scaling data engineering, data science, and machine learning workloads for enterprises.

Industry: Data Infrastructure

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series E+

Headquarters: San Francisco, United States

Founded: 2013

Website LinkedIn