Specialist Solutions Architect - AI/ML
$180,000–$247,500 year
RemoteUnited States
Job Summary
Design and deploy production-level ML and AI architectures using the Databricks unified platform, including AI agents, end-to-end pipeline automation, and model training/inference optimization. Lead GenAI implementation by acting as a hands-on practitioner for enterprise solutions, covering Retrieval-Augmented Generation, tool-calling orchestration, guardrails, and observability systems. Build and maintain scalable customer AI workloads while applying best-in-class MLOps practices across diverse industry domains. Partner with Solutions Architects during the sales cycle to guide prospects through feature engineering, model tracking, and serving within a single platform. Translate customer feedback into actionable product insights by collaborating with Engineering and Product teams to shape the future of Databricks' AI offerings. This role requires 5+ years of hands-on experience in ML or AI engineering, the ability to travel up to 30%, and hitting role-specific milestones within the first six months.
Required Qualifications
- 5+ years of hands-on industry experience in at least one of the following domains: ML Engineering: Building and maintaining cloud infrastructure (AWS, Azure, or GCP) supporting production ML applications and drift monitoring.
- 5+ years of hands-on industry experience in at least one of the following domains: AI Engineering: Working with LLMs and agentic systems, including vector databases, fine-tuning, AI guardrails, and frameworks like LangChain, Hugging Face, or OpenAI APIs.
- Demonstrated ability to translate complex AI/ML concepts for both technical and non-technical audiences.
- Understanding of modern lakehouse architectures (Delta Lake, data modeling, BI integration) across major cloud platforms (AWS, Azure, or GCP).
- Ability to travel up to 30% as needed for customer engagements.
- Ability to hit role-specific training and technical delivery milestones within the first 6 months.
Desired Qualifications
- [Preferred] Prior experience in a pre-sales or post-sales technical consulting role.
- Graduate degree in Computer Science, Engineering, Statistics, or a related quantitative field—or equivalent practical experience.
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