Specialist Solutions Architect - Ai/ml

Databricks Databricks · Data AI · Bangalore, India · Field Engineering - Other

Databricks is seeking an AI/ML Specialist Solutions Architect to guide customers in architecting production-grade ML & AI applications on their platform, focusing on GenAI, MLOps, and end-to-end ML pipelines. The role involves serving as a trusted practitioner for enterprise GenAI solutions, including RAG, agentic systems, and AI evaluation, while also building and optimizing customer AI workloads and providing technical support during the sales process.

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 a 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

  • 5+ years of hands-on industry ML experience
  • Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike

Nice to have

  • Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience
  • 2+ 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
  • Can travel up to 30% when needed

What the JD emphasized

  • production-grade ML & AI applications
  • production-level ML & AI workloads
  • enterprise GenAI solutions
  • agentic systems
  • tool-calling agents
  • multi-agent orchestration
  • AI evaluation and observability
  • productionize these workloads
  • technical sale
  • feature engineering
  • training
  • tracking
  • serving
  • model monitoring

Other signals

  • Architect production-grade ML & AI applications
  • trusted technical ML & AI expert
  • customer roadmap alignment
  • GenAI solutions
  • MLOps