Senior Specialist Solutions Architect - AI & ML Engineer

Databricks Databricks · Data AI · Sweden · Remote · Field Engineering - Other

Senior Specialist Solutions Architect focusing on AI & ML Engineering for Databricks customers. The role involves architecting production-grade ML/AI workloads, including GenAI solutions like RAG and agents, optimizing training and inference, and applying MLOps best practices. It requires deep technical expertise in ML/AI, customer-facing skills, and collaboration with product and engineering teams to influence the roadmap.

What you'd actually do

  1. 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.
  2. 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
  3. Build, scale, and optimize customer AI workloads and apply best in class MLOps to productionize these workloads across a variety of domains
  4. 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
  5. 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

Skills

Required

  • 7+ years of hands-on industry ML experience
  • Architecting production-grade ML & AI applications
  • GenAI
  • MLOps
  • End-to-end ML pipelines
  • Training/inference optimization
  • RAG architectures
  • Agentic systems
  • Tool-calling agents
  • Multi-agent orchestration
  • Guardrails
  • AI evaluation
  • Observability
  • Monitoring systems
  • Feature engineering
  • Model monitoring
  • Technical communication

Nice to have

  • 5+ years customer-facing experience in a pre-sales or post-sales role

What the JD emphasized

  • production-grade ML & AI applications
  • production level ML & AI workloads
  • enterprise GenAI solutions
  • productionize these workloads
  • technical sale

Other signals

  • Architect production-grade ML & AI applications
  • Guide enterprise and strategic customers
  • Work with Solution Architects