Sr. Specialist Solutions Architect
Databricks15 hours ago
Zürich, SwitzerlandSenior
Responsibilities
- Lead discovery, architecture design, demos, proofs of concept, and MVPs for agent, GenAI, and ML use cases.
- Design production-grade agents and multi-agent applications using Databricks AI platform capabilities.
- Help customers implement evaluation, tracing, observability, regression testing, release gates, and production monitoring for AI systems.
- Position the AI Gateway for model access control, guardrails, PII protection, usage tracking, and rate limiting.
- Advise customer technical leaders on AI strategy, governance, economics, and architecture trade-offs.
- Enable solutions architects and partners through workshops, reusable assets, and reference architectures.
- Provide structured customer feedback and market requirements to Product Management and Engineering.
- Represent Databricks at executive briefings, meetups, conferences, and in written content.
Requirements
- 7+ years of hands-on experience in machine learning, AI engineering, or data science, including customer-facing technical work such as pre-sales, consulting, or technical leadership.
- Proven experience shipping LLM and agent systems to production, including evaluation, monitoring, and cost management.
- Deep knowledge of tool use, function calling, MCP, agent memory and state, multi-agent orchestration, retrieval, and context design.
- Practical experience with GenAI evaluation, including tracing, LLM-as-a-judge, evaluation datasets, regression testing, and production observability.
- Hands-on experience with at least one modern agent framework, such as LangGraph, OpenAI Agents SDK, Google ADK, or DSPy.
- Understanding of foundation-model providers and open-weight models, including quality, latency, cost, and data-residency trade-offs.
- Strong grounding in classical machine learning and MLOps, including model development, deployment, monitoring, and lifecycle management at scale.
- Strong software engineering skills in Python and SQL, with the ability to build working demo applications quickly.
- Experience with at least one major cloud platform, such as AWS, Azure, or GCP, and modern data platforms.
- Ability to influence technical leaders up to CTO/CDO level and explain complex AI topics in business terms.
- Proven ability to communicate and teach complex technical concepts to technical and non-technical audiences.
Benefits
- Databricks offers comprehensive benefits and perks, with region-specific details provided through the benefits information link.
Tech Stack
Categories
Solutions Engineering
About Databricks
Databricks builds a cloud-based data and AI platform centered on the lakehouse architecture, combining data engineering, analytics, and machine learning with Apache Spark, Delta Lake, and MLflow. It sells subscriptions and cloud services to enterprises that need to unify data pipelines and develop large-scale AI and analytics. Founded in 2013 by the creators of Apache Spark and headquartered in San Francisco, the company is privately held and serves organizations across many industries.